CN108563200B - Multi-target workpiece scheduling method and device based on ant colony algorithm - Google Patents
Multi-target workpiece scheduling method and device based on ant colony algorithm Download PDFInfo
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Abstract
The invention discloses a multi-target workpiece scheduling method and device based on an ant colony algorithm, wherein the method comprises the following steps: establishing a first preset number of ants and establishing a blank batch during the current iteration; acquiring an pheromone matrix and a target preference vector, and acquiring current processing equipment; taking the empty batch as a first current batch of the current processing equipment; dispatching a first workpiece to be processed into a first current batch; adding the second workpieces to be processed into the current candidate list until all the second workpieces to be processed are scheduled; updating the pheromone matrix of the next iteration of the current iteration; judging whether the iteration number corresponding to the current iteration is equal to a second preset threshold value or not; if not, updating the iteration times, and returning to the step of establishing the empty batch; and if so, taking the global optimal completion time length and the scheduling scheme corresponding to the global optimal energy consumption in the current iteration process as a target scheduling method. By applying the embodiment of the invention, the multi-target scheduling of the workpieces can be realized.
Description
Technical Field
The invention relates to a multi-target workpiece scheduling method, in particular to an ant colony algorithm-based multi-target workpiece scheduling method and device.
Background
The problem of batch processor scheduling (batch scheduling for short) is a kind of combinatorial optimization problem with a strong application background, and exists in many fields in real life, such as the washing processing field of sterilization service in hospitals or the processing field of workpieces. In the field of washing processes for hospital sterilization services, for example, it is necessary to sterilize and disinfect reusable medical instruments after a surgical operation is completed, because they are reused after sterilization. The importance of each package varies, and the duration of washing each package is different. The washing apparatuses have a fixed capacity, as long as the capacity is not exceeded, they can treat a plurality of packages simultaneously. In addition, due to the organization and traceability required in the medical device specific requirements, a kit can usually only be washed in one washing apparatus, not allowed to be separated. Therefore, whether these washing apparatuses can be used for washing with high efficiency will seriously affect the efficiency of the sterilization treatment. By considering the set as a workpiece and the automatic washing equipment as a batch processor, the set washing problem can be abstracted into the minimization of the total weighted completion duration of the workpiece on the parallel batch processor. Moreover, the total weighted completion duration (also referred to as weighted running time) of the workpiece is also a key parameter for reducing the cost of the processing inventory, and therefore, solving the problem is very important for realizing efficient management and scheduling of resources. In addition, in practical applications, a batch processor can be regarded as a processing device.
Currently, ant colony algorithm is commonly used for batch scheduling design. Generally, in each iteration process, a plurality of batches are constructed for each processing equipment in a preset number of processing equipment corresponding to each ant, and then the workpieces to be processed are dispatched to all the batches corresponding to the ants; and sequentially constructing batches of all ants and scheduling workpieces to be processed. And then, taking the corresponding global optimal solution of the current iteration as the basis for updating the pheromone matrix in the next iteration, and further performing the next iteration until the global optimal solution is selected in the last iteration. It should be noted that the global optimal solution is an optimal solution generated in the process from the first iteration to the current iteration.
In the prior art, scheduling of batch processors is performed based on the consistency of the power of each batch processor, i.e., the processing equipment, and single-target optimization, i.e., optimization of the processing duration, is performed. However, in a practical application scenario, the powers of the processing devices may differ, and scheduling according to the scheduling method in the prior art may have a problem that although the processing time is shortest, the energy consumption is high, and multi-objective optimization cannot be considered at the same time, that is, optimization of the processing time and the energy consumption of the processing devices, so how to perform multi-objective workpiece scheduling is a technical problem to be solved urgently.
Disclosure of Invention
The invention aims to provide a multi-target workpiece scheduling method and device based on an ant colony algorithm to realize multi-target workpiece scheduling.
The invention solves the technical problems through the following technical scheme:
the embodiment of the invention provides an ant colony algorithm-based multi-target workpiece scheduling method, which comprises the following steps:
establishing a first preset number of ants during the current iteration, and establishing a blank batch aiming at the current ant in the first preset number of ants;
acquiring an pheromone matrix of each target in the multiple targets and preset target preference vectors aiming at the current ants, acquiring a processing device with the minimum sum of products of each target and the corresponding target preference vectors aiming at each processing device in a second preset number of processing devices, and taking the processing device as the current processing device; wherein the target comprises: energy consumption and processing time;
taking the empty batch as a first current batch of the current processing equipment; dispatching a first workpiece to be machined in the workpieces to be machined to the first current batch; adding a second workpiece to be processed, except the first workpiece to be processed, in the workpieces to be processed into a current candidate list corresponding to the first current batch;
judging whether a workpiece to be processed which is not scheduled exists or not;
if yes, returning to the step of establishing the empty batch aiming at the current ants in the first preset number of ants; scheduling the workpieces to be processed into the batch corresponding to the current ants;
if not, taking one ant except the current ant in the first preset number of ants as the current ant, and returning to the step of establishing the empty batch aiming at the current ant in the first preset number of ants until the workpieces to be processed corresponding to the first preset number of ants are all dispatched;
taking the smaller value of the minimum value of the completion time length obtained in the current iteration process and the minimum value of the completion time length obtained in all iteration processes before the current iteration as the global optimal completion time length corresponding to the current iteration; taking the smaller value of the minimum value of the energy consumption obtained in the current iteration process and the minimum value of the energy consumption obtained in all iteration processes before the current iteration as the global optimal energy consumption corresponding to the current iteration;
taking the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process;
updating the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate and the solution set corresponding to the current iteration;
judging whether the iteration number corresponding to the current iteration is equal to a second preset threshold value or not;
if not, taking the sum of the iteration times corresponding to the current iteration and a first preset threshold value as the iteration times corresponding to the current iteration, and returning to execute the step of establishing a first preset number of ants and establishing an empty batch for the current ant in the first preset number of ants when the current iteration is executed;
and if so, taking the global optimal completion time length and the scheduling scheme corresponding to the global optimal energy consumption in the current iteration process as a target scheduling method.
Optionally, in a specific implementation manner of the embodiment of the present invention, the adding, to the current candidate list corresponding to the first current batch, a second workpiece to be processed, which is to be processed except the first workpiece to be processed, in the workpieces to be processed includes:
adding second workpieces to be machined, except the first workpieces to be machined, in the workpieces to be machined into a current candidate list corresponding to the first current batch, wherein the size of each second workpiece to be machined is smaller than the residual capacity of the current machining equipment; the residual capacity of the current processing equipment is the difference between the total capacity of the current processing equipment and the total size of the first workpiece to be processed;
calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to each second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration, and dispatching the second workpiece to be machined corresponding to the maximum probability to the first current batch;
taking the set of the second workpiece to be machined with the maximum transition probability and the first workpiece to be machined as a first workpiece to be machined, adding the second workpiece to be machined except the first workpiece to be machined in the workpiece to be machined into a candidate list corresponding to the first current batch, and taking the candidate list corresponding to the first current batch as a current candidate list; and returning to execute the step of calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration until the residual capacity of the first current batch is smaller than the size of any one workpiece to be machined.
Optionally, in a specific implementation manner of the embodiment of the present invention, the calculating, according to an pheromone matrix of each target corresponding to each second workpiece to be processed in the current candidate list, an pheromone weight of each target corresponding to the second workpiece to be processed, and heuristic information about a completion duration of the second workpiece to be processed, a probability that the second workpiece to be processed is scheduled in the first current batch includes:
by means of the formula (I) and (II),
calculating a selected probability that a second workpiece to be processed in the candidate workpiece set is scheduled to the first current lot, wherein,
Optionally, in a specific implementation manner of the embodiment of the present invention, the updating, according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate, and the set of solutions corresponding to the current iteration, the pheromone matrix of the next iteration of the current iteration includes:
by means of the formula (I) and (II),
updating the pheromone matrix of a next iteration of the current iteration, wherein,
Optionally, in a specific implementation manner of the embodiment of the present invention, in a case that a determination result of determining whether there is an unscheduled workpiece to be processed is negative, the method further includes:
this sorts the batches corresponding to the current ants in order of their arrival times from small to large.
Optionally, in a specific implementation manner of the embodiment of the present invention, the taking the scheduling scheme corresponding to all ants in the current iteration process as a solution set of the current iteration process includes:
taking the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process; and deleting the scheduling scheme corresponding to the solution set in which the pareto is dominated, and taking the solution set in which the scheduling scheme corresponding to the solution in which the pareto is dominated is deleted as the solution set of the current iteration process.
The embodiment of the invention also provides a multi-target workpiece scheduling device based on the ant colony algorithm, which comprises: an establishing module, an obtaining module, a scheduling module, a first judging module, a first setting module, a second setting module, a third setting module, an updating module, a second judging module, a fourth setting module and a fifth setting module, wherein,
the establishing module is used for establishing a first preset number of ants during current iteration and establishing a blank batch aiming at the current ants in the first preset number of ants;
the acquisition module is used for acquiring an pheromone matrix of each target in the multiple targets and preset target preference vectors aiming at the current ants, acquiring the processing equipment with the minimum sum of products of each target and the corresponding target preference vectors aiming at each processing equipment in a second preset number of processing equipment, and taking the processing equipment as the current processing equipment; wherein the target comprises: energy consumption and processing time;
the scheduling module is used for taking the empty batch as a first current batch of the current processing equipment; dispatching a first workpiece to be machined in the workpieces to be machined to the first current batch; adding a second workpiece to be processed, except the first workpiece to be processed, in the workpieces to be processed into a current candidate list corresponding to the first current batch;
the first judgment module is used for judging whether a workpiece to be processed which is not scheduled exists or not; if yes, triggering the establishing module; if not, triggering the first setting module;
the first setting module is used for taking one ant except the current ant in a first preset number of ants as the current ant and triggering the establishing module until the workpieces to be processed corresponding to the first preset number of ants are all dispatched;
the second setting module is used for taking the smaller value of the minimum value of the completion time length obtained in the current iteration process and the minimum value of the completion time length obtained in all iteration processes before the current iteration as the global optimal completion time length corresponding to the current iteration; taking the smaller value of the minimum value of the energy consumption obtained in the current iteration process and the minimum value of the energy consumption obtained in all iteration processes before the current iteration as the global optimal energy consumption corresponding to the current iteration;
the third setting module is configured to use the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process;
the updating module is used for updating the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate and the solution set corresponding to the current iteration;
the second judging module is used for judging whether the iteration number corresponding to the current iteration is equal to a second preset threshold value or not; if not, triggering the fourth setting module; if so, triggering the fifth setting module, wherein,
the fourth setting module is used for taking the sum of the iteration number corresponding to the current iteration and a first preset threshold value as the iteration number corresponding to the current iteration and triggering the establishing module;
and the fifth setting module is used for taking the global optimal completion time length and the scheduling scheme corresponding to the global optimal energy consumption in the current iteration process as a target scheduling method.
Optionally, in a specific implementation manner of the embodiment of the present invention, the scheduling module is further configured to:
adding second workpieces to be machined, except the first workpieces to be machined, in the workpieces to be machined into a current candidate list corresponding to the first current batch, wherein the size of each second workpiece to be machined is smaller than the residual capacity of the current machining equipment; the residual capacity of the current processing equipment is the difference between the total capacity of the current processing equipment and the total size of the first workpiece to be processed;
calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to each second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration, and dispatching the second workpiece to be machined corresponding to the maximum probability to the first current batch;
taking the set of the second workpiece to be machined with the maximum transition probability and the first workpiece to be machined as a first workpiece to be machined, adding the second workpiece to be machined except the first workpiece to be machined in the workpiece to be machined into a candidate list corresponding to the first current batch, and taking the candidate list corresponding to the first current batch as a current candidate list; and returning to execute the step of calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration until the residual capacity of the first current batch is smaller than the size of any one workpiece to be machined.
Optionally, in a specific implementation manner of the embodiment of the present invention, the scheduling module is further configured to:
by means of the formula (I) and (II),
calculating a selected probability that a second workpiece to be processed in the candidate workpiece set is scheduled to the first current lot, wherein,
Optionally, in a specific implementation manner of the embodiment of the present invention, the update module is further configured to:
by means of the formula (I) and (II),
updating the pheromone matrix of a next iteration of the current iteration, wherein,
Compared with the prior art, the invention has the following advantages:
by applying the embodiment of the invention, the target preference vectors are set for all targets, and then the processing equipment corresponding to the empty lot is selected according to the set target preference vectors, so that the processing equipment for multi-target optimization can be screened out, and further, the multi-target scheduling of the workpiece is realized.
Drawings
Fig. 1 is a schematic flowchart of a multi-objective workpiece scheduling method based on an ant colony algorithm according to an embodiment of the present invention;
fig. 2a is a schematic diagram of a batch corresponding to current ants before being sorted according to an embodiment of the present invention;
fig. 2b is a schematic diagram illustrating a batch of current ants sorted according to an embodiment of the present invention;
fig. 3 is a schematic diagram illustrating an optimization effect of a multi-objective workpiece scheduling method based on an ant colony algorithm in comparison with the prior art according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a multi-objective workpiece scheduling device based on an ant colony algorithm according to an embodiment of the present invention.
Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
In order to solve the problems in the prior art, embodiments of the present invention provide a method and an apparatus for ant colony algorithm-based multi-target workpiece scheduling, and first introduce the ant colony algorithm-based multi-target workpiece scheduling method provided in the embodiments of the present invention.
Fig. 1 is a schematic flowchart of a multi-objective workpiece scheduling method based on an ant colony algorithm according to an embodiment of the present invention; as shown in fig. 1, the method includes:
s101: and during the current iteration, establishing a first preset number of ants, and establishing an empty batch aiming at the current ant in the first preset number of ants.
Specifically, take the first iteration as an example, and take the first iteration as the current iteration. At the beginning of the current iteration, a ants are established. Each ant can be numbered as: 1. 2, 3, … …, a. And then taking the ant-1 with the number of 1 as the current ant, and establishing an empty batch for the ant, wherein the identification information of the empty batch is batch-1.
It is to be understood that an empty lot may be understood as a form of lot that may include empty lots that have already been scheduled with workpieces to be processed and empty lots that have not been scheduled with workpieces to be processed. In addition, the capacity of the empty lot is not greater than the capacity of the processing equipment; for example, if the capacity of the processing equipment is 100 units of workpieces to be processed, the capacity of the empty lot may be less than or equal to the capacity of the processing equipment. The capacity of the processing equipment may or may not be fully utilized in scheduling.
The dimension s of each workpiece to be machined may be different. In addition, the step of establishing the empty batch for the a ants can be executed in parallel, or can be sequentially executed from the 1 st ant according to the sequence of the serial numbers of the ants from small to large; or the ant numbers can be sequentially carried out from the a-th ant in the descending order of the ant numbers; the embodiments of the present invention do not limit this.
S102: acquiring an pheromone matrix of each target in the multiple targets and preset target preference vectors aiming at the current ants, acquiring a processing device with the minimum sum of products of each target and the corresponding target preference vectors aiming at each processing device in a second preset number of processing devices, and taking the processing device as the current processing device; wherein the target comprises: energy consumption and processing time.
In practical applications, at the first iteration, the values of the elements in the pheromone matrix of each target may be preset, set to values between 0 and 1, for example, set to 0.1; at its current iteration, except for the first iteration, the pheromone matrix of the current iteration is the pheromone matrix of the last iteration of the current iteration. For example, the pheromone matrix of each target at iteration 8 is the pheromone matrix updated at iteration 7.
In addition, the target preference vector of the current ant may be a one-dimensional matrix composed of preset preference values of the current ant for each target, for example, the preference vector corresponding to the current ant a for the completion duration a
Can be 0.6, the preference amount of the current ant a corresponding to the completion time A
May be 0.4; thereby further comprising
And
composing a target preference vector for a current ant
The above preference values indicate that the completion duration is emphasized in the scheduling scheme corresponding to the current ants.
It should be noted that the sum of the values of the preference amounts corresponding to the respective targets of any one ant is 1.
S103: taking the empty batch as a first current batch of the current processing equipment; dispatching a first workpiece to be machined in the workpieces to be machined to the first current batch; and adding second workpieces to be processed except the first workpieces to be processed into a current candidate list corresponding to the first current batch in the workpieces to be processed.
Specifically, second workpieces to be machined, except for the first workpiece to be machined, in the workpieces to be machined may be added to the current candidate list corresponding to the first current batch, and the size of each second workpiece to be machined is smaller than the remaining capacity of the current machining equipment; the residual capacity of the current processing equipment is the difference between the total capacity of the current processing equipment and the total size of the first workpiece to be processed;
calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to each second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration, and dispatching the second workpiece to be machined corresponding to the maximum probability to the first current batch;
taking the set of the second workpiece to be machined with the maximum transition probability and the first workpiece to be machined as a first workpiece to be machined, adding the second workpiece to be machined except the first workpiece to be machined in the workpiece to be machined into a candidate list corresponding to the first current batch, and taking the candidate list corresponding to the first current batch as a current candidate list; and returning to execute the step of calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration until the residual capacity of the first current batch is smaller than the size of any one workpiece to be machined.
In particular, a formula may be used,
calculating a selected probability that a second workpiece to be processed in the candidate workpiece set is scheduled to the first current lot, wherein,
In an exemplary manner, the first and second electrodes are,
the first step is as follows: and taking the batch-1 established in the step S101 as the current processing equipment corresponding to the ant-1, namely the first current batch of the processing equipment-1. And then randomly selecting a workpiece-1 from the n workpieces to be processed as a first workpiece to be processed and dispatching the workpiece-1 into the batch-1.
Since the workpiece-1 of the n workpieces to be machined is dispatched into the lot-1, n-1 workpieces to be machined remain among the n workpieces to be machined. Constructing a candidate list-1 for batch-1; and selecting the workpieces to be machined from the remaining n-1 workpieces to be machined, and adding the workpieces to be machined into the candidate list-1.
The workpieces to be machined that are added to the candidate list-1 need to satisfy: the sum of the sizes of all the second workpieces to be machined in the candidate list-1 cannot exceed the remaining capacity of the machining apparatus-1, where the remaining capacity is the total capacity of the machining apparatus-1 minus the size of the workpieces to be machined that have been scheduled to the machining apparatus.
In the second step, the data can be represented by a formula,
calculating a selected probability that a second workpiece to be processed of the candidate list-1 is scheduled to lot-1, wherein,
The third step:
after the transition probabilities of all the second workpieces to be processed in the current candidate list and the candidate list-1 are calculated, scheduling j second workpieces to be processed with the numbers of the largest transition probabilities into batch-1, wherein the second workpieces to be processed j are scheduled into batch-1, and the first workpieces to be processed corresponding to the new batch-1 comprise the second workpieces to be processed j and the previous first workpieces to be processed. Adding second workpieces to be processed, except the first workpieces to be processed, in the workpieces to be processed which are not scheduled into a new candidate list-2 corresponding to the first current batch, wherein the size of each second workpiece to be processed in the new candidate list-2 is smaller than the residual capacity of the new batch-1; new batch-1 is taken as the first current batch and new candidate list-2 is taken as the current candidate list. In practical application, the new candidate list-2 may be used as the current candidate list in the next step, that is, the candidate list-1, and the step of performing the third step is returned until the remaining capacity of the first current batch is smaller than the size of any one of the workpieces to be processed.
It is understood that the remaining capacity of the first current lot is smaller than the size of any one of the workpieces to be processed, and may be that the remaining capacity of the first current lot is zero; or the remaining capacity of the first current batch is not sufficient to accommodate any one of said workpieces to be machined.
S104: judging whether a workpiece to be processed which is not scheduled exists or not; if yes, executing S101; if not, executing S105: .
For example, after the scheduling process for lot-1 is finished, it is determined whether there is an unscheduled workpiece to be processed, and if so, step S105 is executed.
S105: and taking one of the ants except the current ant in the first preset number of ants as the current ant, and returning to the step of establishing the empty batch aiming at the current ant in the first preset number of ants until the workpieces to be processed corresponding to the first preset number of ants are all dispatched.
Exemplarily, the next ant of the ant-1, the ant-2 is taken as the current ant, and the step S101 is executed again. And dispatching the workpieces to be processed corresponding to the ants in the first preset number.
For example, n workpieces to be processed corresponding to the ant-1 are all dispatched to the batch corresponding to the ant-1; similarly, each of the n workpieces to be processed corresponding to the ant-2 is dispatched to the batch corresponding to the ant-2.
In a specific implementation of the embodiment of the present invention, the batches corresponding to the current ants are sorted in order of their arrival times from small to large.
For example, fig. 2a is a schematic diagram of a batch corresponding to current ants according to an embodiment of the present invention before sorting, as shown in fig. 2a, t is a time axis. After the current ants are dispatched to the n workpieces to be processed, the n workpieces to be processed are dispatched to five batches, wherein one batch B exists in the five batches11Batch B21Is dispatched to the processing equipment M1(ii) a And M1In the processing sequence of lot B11Batch B21(ii) a Batch B11With an arrival time of 3, batch B21Is 12. Batch B12Batch B22Batch B32Is dispatched to the processing equipment M2(ii) a And M2In the processing sequence of lot B12Batch B22Batch B32(ii) a Batch B12Has an arrival time of 5, lot B22Has an arrival time of 2, lot B32Is 3.
As can be appreciated, the arrival time is the time it takes for the workpiece to be processed to be dispatched to the processing tool.
Fig. 2b is a schematic diagram of a process of sorting batches corresponding to current ants according to an embodiment of the present invention, where in fig. 2b, the order of the batches sorted according to arrival time is:
machining apparatus M1: batch B22Batch B32Batch B12；
Machining apparatus M2：B11Batch B21。
By applying the embodiment of the invention, the batches of the processing equipment corresponding to each ant can be sequenced, so that the batches with short arrival time are processed preferentially, and the processing time is shortened.
S106: taking the smaller value of the minimum value of the completion time length obtained in the current iteration process and the minimum value of the completion time length obtained in all iteration processes before the current iteration as the global optimal completion time length corresponding to the current iteration; and taking the smaller value of the minimum value of the energy consumption obtained in the current iteration process and the minimum value of the energy consumption obtained in all iteration processes before the current iteration as the global optimal energy consumption corresponding to the current iteration.
Illustratively, calculating the completion time length corresponding to each ant in the 10 th iteration process, for example, the minimum completion time length is ant-4; comparing the completion time length of the ant-4 with the minimum value of the completion time length in the previous 9 iteration processes, and if the completion time length of the ant-4 is the shortest, taking the completion time length corresponding to the ant-4 as the global optimal completion time length corresponding to the 10 th iteration; and if the completion time length of the ant-4 is longer than the completion time length in the previous 9 iteration processes, taking the completion time length in the previous 9 iteration processes as the global optimal completion time length corresponding to the 10 th iteration.
Similarly, the energy consumption values corresponding to the ants during the 10 th iteration are also processed as described above.
It can be understood that the global optimal energy consumption value is the minimum energy consumption value in all iteration processes before the current iteration; similarly, the completion time period is the minimum completion time period during all iterations preceding the current iteration.
S107: and taking the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process.
In a specific implementation manner of the embodiment of the present invention, the scheduling schemes corresponding to all ants in the current iteration process may be used as a solution set of the current iteration process; and deleting the scheduling scheme corresponding to the solution set in which the pareto is dominated, and taking the solution set in which the scheduling scheme corresponding to the solution in which the pareto is dominated is deleted as the solution set of the current iteration process.
S108: and updating the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate and the solution set corresponding to the current iteration.
In particular, a formula may be used,
updating the pheromone matrix of a next iteration of the current iteration, wherein,
S109: judging whether the iteration number corresponding to the current iteration is equal to a second preset threshold value or not; if not, executing S1010; if yes, go to step S1011.
Illustratively, comparing the iteration number of the current iteration with a second preset threshold value according to the iteration number of the current iteration, and judging whether the iteration number of the current iteration is equal to the second preset threshold value, if so, indicating that the iteration number has reached the maximum iteration number, and executing step S1012; if not, the iteration count is not yet reached to the maximum iteration count, and step S1011 is executed.
S1010: and taking the sum of the iteration number corresponding to the current iteration and the first preset threshold value as the iteration number corresponding to the current iteration, and returning to execute the step S101.
Illustratively, the iteration number corresponding to the current iteration is 1, if the preset value is 1, taking 1-2 as the iteration number of the next iteration of the first iteration, and returning to execute the step S101.
In practical application, the iteration number corresponding to the first iteration may be represented by 100, the iteration number corresponding to the second iteration may be represented by 400, the iteration number corresponding to the third iteration may be represented by 700, and the corresponding preset value is 300. The embodiment of the invention does not limit the representation mode of the iteration times.
S1011: and taking the global optimal completion duration and the scheduling scheme corresponding to the global optimal energy consumption in the current iteration process as a target scheduling method.
Illustratively, if the 45 th iteration is the maximum iteration number, the corresponding relation between the workpiece to be processed and the processing equipment, which corresponds to the ant with the minimum overall optimal energy consumption and the optimal completion time length in the 45 th iteration, is used as a target scheduling method.
It can be understood that the target scheduling method obtained in step S1011 has the best balance of time-out duration and energy consumption since the time-out duration and the energy consumption have corresponding weights, respectively. Of course, in practical application, a larger weight may be set for the completion time to obtain the target scheduling method with a shorter completion time.
In practical application, the scheduling method corresponding to the set of solutions obtained in the current iteration process may also be used as the target scheduling method.
Fig. 3 is a schematic diagram illustrating an optimization effect of the multi-objective workpiece scheduling method based on the ant colony algorithm in comparison with the prior art, as shown in fig. 3, 301 is energy consumption and processing duration corresponding to the workpiece scheduling method obtained by applying the embodiment of the present invention; 302 is energy consumption and processing duration corresponding to a workpiece scheduling method obtained by applying the prior art, wherein the horizontal axis is completion time; the vertical axis is the machine energy consumption. Obviously, compared with the prior art, the method and the device reduce the energy consumption of the machine and the processing time.
In addition, it can be understood that 301 is a set of non-dominated solutions obtained by applying the embodiment of the present invention, and compared with the solution 302 obtained by applying the prior art, the number of non-dominated solutions obtained by applying the embodiment of the present invention is greater, and the solutions corresponding to 302 are dominated by the solution in 301, that is, the quality of the solution obtained by applying the embodiment of the present invention is higher.
It is emphasized that the machine energy consumption is the sum of the energy consumptions of all the processing devices corresponding to the target scheduling method obtained by applying the embodiment of the present invention; the finishing time is a time period from a time corresponding to the first batch to a time corresponding to the last batch.
By applying the embodiment of the invention shown in FIG. 1, the processing equipment for multi-target optimization can be screened out by setting the target preference vector for each target and then selecting the processing equipment corresponding to the empty lot according to the set target preference vector, thereby realizing multi-target scheduling of the workpiece.
Corresponding to the embodiment shown in fig. 1 of the invention, the embodiment of the invention also provides an ant colony algorithm-based multi-target workpiece scheduling device.
Fig. 4 is a schematic structural diagram of a multi-objective workpiece scheduling apparatus based on an ant colony algorithm according to an embodiment of the present invention, as shown in fig. 4, the apparatus includes: a setup module 201, an acquisition module 202, a scheduling module 203, a first judgment module 204, a first setup module 205, a second setup module 206, a third setup module 207, an update module 208, a second judgment module 209, a fourth setup module 2010, and a fifth setup module 2011, wherein,
the establishing module 201 is configured to establish a first preset number of ants during a current iteration, and establish a blank batch for a current ant of the first preset number of ants;
the obtaining module 202 is configured to obtain an pheromone matrix of each target of the multiple targets and a preset target preference vector for the current ant, and obtain, for each processing device of a second preset number of processing devices, a processing device with a smallest sum of products of each target and a corresponding target preference vector, and use the processing device as a current processing device; wherein the target comprises: energy consumption and processing time;
the scheduling module 203 is configured to use the empty lot as a first current lot of the current processing equipment; dispatching a first workpiece to be machined in the workpieces to be machined to the first current batch; adding a second workpiece to be processed, except the first workpiece to be processed, in the workpieces to be processed into a current candidate list corresponding to the first current batch;
the first judging module 204 is configured to judge whether there is an unscheduled workpiece to be processed; if yes, triggering the establishing module 201; if not, triggering the first setting module 205;
the first setting module 205 is configured to use one of a first preset number of ants, except the current ant, as the current ant, and trigger the establishing module 201 until the workpieces to be processed corresponding to the first preset number of ants are all scheduled;
the second setting module 206 is configured to use a smaller value of the minimum value of the completion duration obtained in the current iteration process and the minimum values of the completion durations obtained in all iteration processes before the current iteration as the global optimal completion duration corresponding to the current iteration; taking the smaller value of the minimum value of the energy consumption obtained in the current iteration process and the minimum value of the energy consumption obtained in all iteration processes before the current iteration as the global optimal energy consumption corresponding to the current iteration;
the third setting module 207 is configured to use the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process;
the updating module 208 is configured to update the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate, and the set of solutions corresponding to the current iteration;
the second determining module 209 is configured to determine whether the iteration number corresponding to the current iteration is equal to a second preset threshold; if not, triggering the fourth setting module 2010; if so, the fifth setup module 2011 is triggered, wherein,
the fourth setting module 2010 is configured to use a sum of the iteration count corresponding to the current iteration and a first preset threshold as the iteration count corresponding to the current iteration, and trigger the establishing module 201;
the fifth setting module 2011 is configured to use the scheduling scheme corresponding to the global optimal completion duration and the global optimal energy consumption in the current iteration process as the target scheduling method.
By applying the embodiment shown in FIG. 4 of the invention, the processing equipment for multi-target optimization can be screened out by setting the target preference vector for each target and then selecting the processing equipment corresponding to the empty lot according to the set target preference vector, thereby realizing multi-target scheduling of the workpiece.
In a specific implementation manner of the embodiment of the present invention, the scheduling module 203 is further configured to:
adding second workpieces to be machined, except the first workpieces to be machined, in the workpieces to be machined into a current candidate list corresponding to the first current batch, wherein the size of each second workpiece to be machined is smaller than the residual capacity of the current machining equipment; the residual capacity of the current processing equipment is the difference between the total capacity of the current processing equipment and the total size of the first workpiece to be processed;
calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to each second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration, and dispatching the second workpiece to be machined corresponding to the maximum probability to the first current batch;
taking the set of the second workpiece to be machined with the maximum transition probability and the first workpiece to be machined as a first workpiece to be machined, adding the second workpiece to be machined except the first workpiece to be machined in the workpiece to be machined into a candidate list corresponding to the first current batch, and taking the candidate list corresponding to the first current batch as a current candidate list; and returning to execute the step of calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration until the residual capacity of the first current batch is smaller than the size of any one workpiece to be machined.
In a specific implementation manner of the embodiment of the present invention, the scheduling module 203 is further configured to:
by means of the formula (I) and (II),
calculating a selected probability that a second workpiece to be processed in the candidate workpiece set is scheduled to the first current lot, wherein,
In a specific implementation manner of the embodiment of the present invention, the updating module 208 is further configured to:
by means of the formula (I) and (II),
updating the pheromone matrix of a next iteration of the current iteration, wherein,
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A multi-target workpiece scheduling method based on an ant colony algorithm is characterized by comprising the following steps:
establishing a first preset number of ants during the current iteration, and establishing a blank batch aiming at the current ant in the first preset number of ants;
acquiring an pheromone matrix of each target in the multiple targets and preset target preference vectors aiming at the current ants, acquiring a processing device with the minimum sum of products of each target and the corresponding target preference vectors aiming at each processing device in a second preset number of processing devices, and taking the processing device as the current processing device; wherein the target comprises: energy consumption and processing time;
taking the empty batch as a first current batch of the current processing equipment; dispatching a first workpiece to be machined in the workpieces to be machined to the first current batch; adding a second workpiece to be processed, except the first workpiece to be processed, in the workpieces to be processed into a current candidate list corresponding to the first current batch;
judging whether a workpiece to be processed which is not scheduled exists or not;
if yes, returning to the step of establishing the empty batch aiming at the current ants in the first preset number of ants; scheduling the workpieces to be processed into the batch corresponding to the current ants;
if not, taking one ant except the current ant in the first preset number of ants as the current ant, and returning to the step of establishing the empty batch aiming at the current ant in the first preset number of ants until the workpieces to be processed corresponding to the first preset number of ants are all dispatched;
taking the smaller value of the minimum value of the completion time length obtained in the current iteration process and the minimum value of the completion time length obtained in all iteration processes before the current iteration as the global optimal completion time length corresponding to the current iteration; taking the smaller value of the minimum value of the energy consumption obtained in the current iteration process and the minimum value of the energy consumption obtained in all iteration processes before the current iteration as the global optimal energy consumption corresponding to the current iteration;
taking the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process;
updating the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate and the solution set corresponding to the current iteration;
judging whether the iteration number corresponding to the current iteration is equal to a second preset threshold value or not;
if not, taking the sum of the iteration times corresponding to the current iteration and a first preset threshold value as the iteration times corresponding to the current iteration, and returning to execute the step of establishing a first preset number of ants and establishing an empty batch for the current ant in the first preset number of ants when the current iteration is executed;
if so, taking the global optimal completion duration and the scheduling scheme corresponding to the global optimal energy consumption in the current iteration process as a target scheduling method;
adding a second workpiece to be machined, except the first workpiece to be machined, in the workpiece to be machined into the current candidate list corresponding to the first current batch, wherein the step of adding the second workpiece to be machined into the current candidate list corresponding to the first current batch comprises the following steps:
adding second workpieces to be machined, except the first workpieces to be machined, in the workpieces to be machined into a current candidate list corresponding to the first current batch, wherein the size of each second workpiece to be machined is smaller than the residual capacity of the current machining equipment; the residual capacity of the current processing equipment is the difference between the total capacity of the current processing equipment and the total size of the first workpiece to be processed;
calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to each second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration, and dispatching the second workpiece to be machined corresponding to the maximum probability to the first current batch;
taking a set of a second workpiece to be machined corresponding to the maximum probability and the first workpiece to be machined as a first workpiece to be machined, adding second workpieces to be machined except the first workpiece to be machined in the workpieces to be machined into a candidate list corresponding to the first current batch, and taking the candidate list corresponding to the first current batch as a current candidate list; and returning to execute the step of calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration until the residual capacity of the first current batch is smaller than the size of any one workpiece to be machined.
2. The ant colony algorithm-based multi-target workpiece scheduling method according to claim 1, wherein the calculating the probability that the second workpiece to be machined is scheduled to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined, and heuristic information about the completion duration of the second workpiece to be machined comprises:
by means of the formula (I) and (II),
calculating a selected probability that a second workpiece to be processed in the candidate workpiece set is scheduled to the first current lot, wherein,
3. The ant colony algorithm-based multi-target workpiece scheduling method according to claim 2, wherein the updating of the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate and the set of solutions corresponding to the current iteration comprises:
by means of the formula (I) and (II),
updating the pheromone matrix of a next iteration of the current iteration, wherein,
4. The ant colony algorithm-based multi-target workpiece scheduling method according to claim 1, wherein in a case that the determination result of determining whether there is an unscheduled workpiece to be processed is no, the method further comprises:
this sorts the batches corresponding to the current ants in order of their arrival times from small to large.
5. The method as claimed in claim 1, wherein the step of using the scheduling schemes corresponding to all ants in the current iteration process as the solution set of the current iteration process comprises:
taking the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process; and deleting the scheduling scheme corresponding to the solution set in which the pareto is dominated, and taking the solution set in which the scheduling scheme corresponding to the solution in which the pareto is dominated is deleted as the solution set of the current iteration process.
6. An ant colony algorithm-based multi-target workpiece scheduling device, comprising: an establishing module, an obtaining module, a scheduling module, a first judging module, a first setting module, a second setting module, a third setting module, an updating module, a second judging module, a fourth setting module and a fifth setting module, wherein,
the establishing module is used for establishing a first preset number of ants during current iteration and establishing a blank batch aiming at the current ants in the first preset number of ants;
the acquisition module is used for acquiring an pheromone matrix of each target in the multiple targets and preset target preference vectors aiming at the current ants, acquiring the processing equipment with the minimum sum of products of each target and the corresponding target preference vectors aiming at each processing equipment in a second preset number of processing equipment, and taking the processing equipment as the current processing equipment; wherein the target comprises: energy consumption and processing time;
the scheduling module is used for taking the empty batch as a first current batch of the current processing equipment; dispatching a first workpiece to be machined in the workpieces to be machined to the first current batch; adding a second workpiece to be processed, except the first workpiece to be processed, in the workpieces to be processed into a current candidate list corresponding to the first current batch;
the first judgment module is used for judging whether a workpiece to be processed which is not scheduled exists or not; if yes, triggering the establishing module; if not, triggering the first setting module;
the first setting module is used for taking one ant except the current ant in a first preset number of ants as the current ant and triggering the establishing module until the workpieces to be processed corresponding to the first preset number of ants are all dispatched;
the second setting module is used for taking the smaller value of the minimum value of the completion time length obtained in the current iteration process and the minimum value of the completion time length obtained in all iteration processes before the current iteration as the global optimal completion time length corresponding to the current iteration; taking the smaller value of the minimum value of the energy consumption obtained in the current iteration process and the minimum value of the energy consumption obtained in all iteration processes before the current iteration as the global optimal energy consumption corresponding to the current iteration;
the third setting module is configured to use the scheduling schemes corresponding to all ants in the current iteration process as a solution set of the current iteration process;
the updating module is used for updating the pheromone matrix of the next iteration of the current iteration according to the pheromone matrix corresponding to the current iteration, the global pheromone volatilization rate and the solution set corresponding to the current iteration;
the second judging module is used for judging whether the iteration number corresponding to the current iteration is equal to a second preset threshold value or not; if not, triggering the fourth setting module; if so, triggering the fifth setting module, wherein,
the fourth setting module is used for taking the sum of the iteration number corresponding to the current iteration and a first preset threshold value as the iteration number corresponding to the current iteration and triggering the establishing module;
the fifth setting module is used for taking the global optimal completion duration and the scheduling scheme corresponding to the global optimal energy consumption in the current iteration process as a target scheduling method;
the scheduling module is further configured to:
adding second workpieces to be machined, except the first workpieces to be machined, in the workpieces to be machined into a current candidate list corresponding to the first current batch, wherein the size of each second workpiece to be machined is smaller than the residual capacity of the current machining equipment; the residual capacity of the current processing equipment is the difference between the total capacity of the current processing equipment and the total size of the first workpiece to be processed;
calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to each second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration, and dispatching the second workpiece to be machined corresponding to the maximum probability to the first current batch;
taking a set of a second workpiece to be machined corresponding to the maximum probability and the first workpiece to be machined as a first workpiece to be machined, adding second workpieces to be machined except the first workpiece to be machined in the workpieces to be machined into a candidate list corresponding to the first current batch, and taking the candidate list corresponding to the first current batch as a current candidate list; and returning to execute the step of calculating the probability that the second workpiece to be machined is dispatched to the first current batch according to the pheromone matrix of each target corresponding to each second workpiece to be machined in the current candidate list, the pheromone weight of each target corresponding to the second workpiece to be machined and heuristic information of the second workpiece to be machined about completion duration until the residual capacity of the first current batch is smaller than the size of any one workpiece to be machined.
7. The ant colony algorithm-based multi-objective workpiece scheduling device according to claim 6, wherein the scheduling module is further configured to:
by means of the formula (I) and (II),
calculating a selected probability that a second workpiece to be processed in the candidate workpiece set is scheduled to the first current lot, wherein,
8. The ant colony algorithm-based multi-objective workpiece scheduling device of claim 7, wherein the updating module is further configured to:
by means of the formula (I) and (II),
updating the pheromone matrix of a next iteration of the current iteration, wherein,
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