CN117519055B

CN117519055B - Parallel assembly line scheduling method and device considering complex man-machine cooperation mode

Info

Publication number: CN117519055B
Application number: CN202311708260.XA
Authority: CN
Inventors: 毛照昉; 张嘉欣; 黄典; 方侃
Original assignee: Tianjin University
Current assignee: Tianjin University
Priority date: 2023-12-12
Filing date: 2023-12-12
Publication date: 2024-05-28
Anticipated expiration: 2043-12-12
Also published as: CN117519055A

Abstract

The invention relates to the technical field of management science, in particular to a parallel assembly line scheduling method and device considering a complex man-machine cooperation mode, comprising the following steps: s1, establishing and analyzing a mixed integer programming model of a parallel assembly line balance problem PALBP-HRC considering a complex man-machine cooperation mode, and decomposing the PALBP-HRC into three sub-problems: a process allocation sub-problem, a robot allocation sub-problem and an intra-station resource scheduling sub-problem; s2, randomly creating a process priority list and a robot list, performing process distribution, generating an initial process distribution list and a process processing mode list, respectively serving as initial solutions of process distribution sub-problems and in-station resource scheduling sub-problems, and taking the randomly generated robot list as the initial solution of the robot distribution sub-problems; s3, based on an improved tabu search algorithm framework, carrying out iterative optimization on initial solutions of the three sub-problems to obtain an optimal scheme. The invention can realize the efficient solution of PALBP-HRC and is beneficial to filling the blank in the current field.

Description

Parallel assembly line scheduling method and device considering complex man-machine cooperation mode

Technical Field

The invention relates to the technical field of management science, in particular to a parallel assembly line scheduling method and device considering a complex man-machine cooperation mode.

Background

Assembly lines have demonstrated their efficiency in the production of standardized, high volume and high quality products, with great attention in both academia and industry for decades. When product requirements exceed the capabilities of a single production system, having multiple assembly lines to produce together is an effective solution. The parallel assembly line balancing problem (Parallel Assembly Line Balancing Problem, PALBP) is a typical form of the multiple line balancing problem, which refers to the parallel running of multiple lines, balanced between the parallel lines using multiple line stations, where the process steps of adjacent lines can be performed together.

With the development of industrial automation and intelligent manufacturing, the collaborative robot provides additional flexibility and efficiency for the production process, can work together with workers safely, can further improve the efficiency of an assembly system by integrating the collaborative robot into a parallel assembly line, can execute different working procedures in parallel, can cooperatively execute the same working procedure, can walk and move between two assembly lines to process working procedures on the two lines, and can be parallel or collaborative with the robot in the process, so that a complex working procedure combination mode is achieved, the common balance of the two parallel lines is realized, and the parallel assembly line balance problem (Parallel Assembly Line Balancing Problem with Human-Robot Collaboration, PALBP-HRC) considering a complex man-machine cooperation mode is realized. Considering the complex man-machine cooperation mode on the parallel assembly line brings greater challenges to the complex parallel assembly line balancing problem, and how to perform parallel assembly line scheduling considering the complex man-machine cooperation mode is a problem to be solved urgently.

Disclosure of Invention

The invention provides a parallel assembly line scheduling method and a parallel assembly line scheduling device considering a complex man-machine cooperation mode, which are used for solving the problems in the prior art, and the technical scheme provided by the invention is as follows:

In one aspect, a parallel assembly line scheduling method considering a complex human-computer cooperation mode is provided, the method comprising:

S1, establishing and analyzing a mixed integer programming model of a parallel assembly line balance problem PALBP-HRC considering a complex man-machine cooperation mode, and decomposing the PALBP-HRC into three sub-problems: a process allocation sub-problem, a robot allocation sub-problem and an intra-station resource scheduling sub-problem;

S2, randomly creating a process priority list and a robot list, performing process distribution, generating an initial process distribution list and a process processing mode list, respectively serving as initial solutions of process distribution sub-problems and in-station resource scheduling sub-problems, and taking the randomly generated robot list as the initial solution of the robot distribution sub-problems;

S3, based on an improved tabu search algorithm framework, carrying out iterative optimization on initial solutions of the three sub-problems to obtain an optimal scheme.

Optionally, the mixed integer programming model is as follows:

index:

i, j Process index, i, j ε {1,2, …, NT }

H Assembly line index, H ε {1, …, H }

K-bit index, k ε {1,2, …, NS }

P-processing mode index, p.epsilon { p _H,p_R,p_C }

Parameters:

I set of procedures on all assembly lines, I= { I ₁,…,I_h }

Procedure set on I _h assembly line h

Number of processes on NT _h assembly line h

K set of stations, K= {1,2, …, NS }

Q number of robots

P set of processing modes, P= { P _H,p_R,p_C }

M is a very large positive number

Time for process i on line h of t _hip to be processed by processing means p

Direct set of preferential relationships between processes on line h of E _h

The variables:

CT beat time

X _hikp binary variable, if process i is assigned to station k on line h, using process pattern p, then the value is 1

Start time of step i s _i

U _hk binary variable, if station k on line h is used, then the value is 1

R _k binary variable, if a collaborative robot is assigned to a workstation k, then the value is 1

Y _ij binary variable, if process I ε I starts before process j ε I (s _i≤s_j), then the value is 1

And (3) model:

Minimize CT (1)

Wherein the objective function (1) is aimed at minimizing the takt time of the parallel assembly line; constraint (2) ensures that each process i on each line h is assigned to a station k for processing by a processing mode p; constraints (3) - (4) are precedence relation constraints, constraint (3) ensures precedence relation between processes on different stations, and a previous process must be allocated to a previous station or the same station as a current process; the constraint condition (4) ensures that the current process can be started only after the previous process is completed on the same station on the same line; constraint (5) ensures that the completion time of each process does not exceed the takt time; constraint (6) - (7) ensures that a worker can only perform a process from an adjacent line; constraints (8) - (13) prevent the simultaneous reuse of the same worker or robot: constraining (8) - (9) to take effect on each line and its adjacent line to ensure that other processes on the same station cannot be processed until the coordinated process is completed; constraints (10) - (11) ensure that the collaboration process cannot be performed due to resource occupation until the previous process is completed; for a pair of processes which are not cooperatively processed, constraints (12) - (13) ensure that when the processes are distributed to the same station and processed by the same worker or robot, the next process can be started after the previous process is completed; constraint (14) ensures that the process can be machined or co-machined by the robot only if the robot is present at the current station; a constraint (15) for limiting the number of robots; constraint (16) defines the sequence of the process steps; the definition of variables is given in constraints (17) - (21).

Optionally, in S2, a process priority list and a robot list are randomly created, and process allocation is performed, so as to generate an initial process allocation list, which specifically includes:

Using a first coding and decoding method, creating separate priority lists randomly for the processes on two lines of a parallel assembly line respectively, calculating the lower bounds of the beat time of the two lines as the initial beat time of the two lines respectively, wherein the initial unassigned process list is all the processes, distributing the processes according to the priority lists of the two lines and the robot list randomly created, and decoding to obtain the beat time by using the following method:

Starting the distribution process from the first station, firstly distributing the processes on the first line to the stations according to the priority list of the first line and the initial beat time of the first line, sequencing the processes according to the descending order of the priority, judging whether all the previous processes with the highest priority are distributed, if all the previous processes are distributed completely, and calculating the station time after the process is distributed to the current station within the initial beat time of the first line by adopting an approximation method: adding the processing time of workers of each working procedure on the first line, distributing the working procedure to the current working position, removing the working procedure from the unassigned working procedure list, otherwise, skipping the working procedure, and distributing the next working procedure arranged in descending order of priority;

If the working procedure which does not meet the condition on the first line can be reassigned to the current working position, the working procedure on the second line is assigned to the working position according to the priority list of the second line, the assignment mode is the same as that of the first line, the initial beat time is the initial beat time of the second line, and the working position time is calculated by adopting an approximation method: adding the working time of workers of each working procedure on the second line, continuously repeating the process, if the working procedure of the current working procedure which does not meet the condition can be distributed, starting the next working procedure, sequentially distributing the working procedures on the first line and the second line, when the working procedure is distributed to the last working procedure, distributing the rest unassigned working procedures on the first line to the last working procedure, judging whether the working procedure time of the last working procedure is within the initial beat time of the first line at the moment, and if so, distributing the working procedure on the current first line to be the initial working procedure distribution of the first line; if not, adding one to the initial beat time of the first line, and repeating the process until all the working procedures on the first line are distributed to the working stations, so as to generate an initial working procedure distribution list on the first line; the remaining unassigned procedures on the second line are also assigned to the last station, whether the station time of the last station is within the initial beat time of the second line at the moment is judged, and if so, the current procedure on the second line is assigned as the procedure of the second line; if not, adding one to the initial beat time of the second line, and repeating the process until all the working procedures on the second line are distributed to the working stations, so as to generate an initial working procedure distribution list on the second line;

Summarizing an initial first-line process distribution list and an initial second-line process distribution list to obtain an initial parallel assembly line process distribution list, wherein the initial parallel assembly line process distribution list comprises initial distribution conditions and processing sequences of processes on all stations, and calculating station time of all stations by adopting an accurate method in combination with a robot distribution list, wherein the maximum station time is takt time obtained by decoding.

Combining all working procedures on two lines of a parallel assembly line by using a second coding and decoding mode, and randomly creating a priority list, wherein the priority value range of the priority list is from 1 to the total number of the working procedures of the two lines, the working procedure number of the second line is followed by the first line, and the lower bound of the takt time after the working procedures on the two lines are summarized is calculated as initial takt time;

The initial unassigned process list is all the processes, and based on this priority list and the randomly created robot list, the processes are assigned and decoded to get the beat time using the following method:

Starting to distribute the working procedure from the first working position, sorting the working procedures according to the descending order of the priority, judging whether all the previous working procedures of the working procedure with the highest priority are distributed, if all the previous working procedures are distributed completely, and the working position time after the working procedure is distributed to the current working position is within the initial beat time, the working position time is calculated by adopting an accurate method, the working procedure is distributed to the current working position, the working procedure is removed from a non-distributed working procedure list, otherwise, the working procedure is skipped, and the next working procedure arranged according to the descending order of the priority is distributed;

The process is repeated continuously, if the current working procedure does not meet the condition, the next working procedure is started, when the working procedure is distributed to the last working procedure, the rest unassigned working procedures are distributed to the last working procedure, whether the working procedure time of the last working procedure is in the initial takt time or not is judged, and if the working procedure time of the last working procedure is in the initial takt time, the current working procedure distribution is the initial working procedure distribution; if not, adding one to the initial takt time, repeating the process until all working procedures are distributed to the working stations and the working station time of each working station is within the current takt time, and generating an initial working procedure distribution list comprising the initial distribution condition and the processing sequence of the working procedures on each working station, wherein the maximum value of the current working station time is the takt time obtained by decoding.

solving a corresponding parallel assembly line balance problem PALBP by using a third coding and decoding mode, converting the process allocation in the obtained optimal solution into a priority list, and calculating the lower bound of the takt time after the process summarization on two lines of the parallel assembly line as the initial takt time;

Optionally, the calculating the lower bound of the takt time of the two lines or the lower bound of the takt time after the process is summarized on the two lines specifically includes:

The lower bound of the takt time is the minimum total machining time divided by the fixed number of stations NS, so that the minimum total machining time is required to divide the process on each assembly line or all the processes on both assembly lines into three different parts: (i) including a worker-only process; (ii) Including all procedures that can be performed by the robot alone; (iii) The method comprises the working procedures that can be cooperatively executed but the robot cannot separately process, and the total processing time of the three parts is respectively recorded as t ₁、t₂、t₃;

In the first case, t ₁ is less than t ₂, to reduce the total machining time, some procedures are transferred from robotic machining to worker machining:

Assuming an ideal case: the number of robots is sufficient, the priority relation among the working procedures is not considered, the working procedures are divided, the working procedures which are processed by the robots can be transferred to workers in half, the total processing time is the smallest compared with the non-ideal situation, and the processing time of the known robots is twice as long as that of the workers, so that t ₂-t₁ is divided into three parts, one part of robots is transferred to two parts of workers, the time of the parallel processing working procedures of the final workers and the robots is equal, the total processing time is reduced, the processing time of the working procedures which move from one side of the robots is (t ₂-t₁)/3, and the total processing time is t ₁+t₃+(t₂-t₁)/3;

in the second case, t ₁ is equal to or greater than t ₂, in which case, since t ₁ is a process that can only be processed by a worker, the total processing time cannot be reduced by moving the process, and the total processing time is t ₁+t₃;

The calculation method of the lower bound of the final beat time is as follows:

Optionally, calculating the station time by an accurate method specifically comprises the following steps:

Looking at whether robots exist on the current station according to the randomly created robot list: if the robot does not exist on the current station, the processing mode of the current working procedure is worker processing; if the robot is arranged on the current station, three possible processing modes of the current working procedure are as follows: worker processing, robot processing and man-machine cooperative processing, and respectively calculating the finishing time of the current working procedure under the three processing modes:

When a worker processes, taking the maximum value of the available time of the worker and the minimum start time as the starting processing time of the current process, adding the processing time of the worker of the known process as the finishing time of the current process, wherein the available time of the worker is the idle starting time of the worker for finishing other processes, and the minimum start time is the last finishing time of the preceding process;

When the robot processes, taking the maximum value of the available time and the minimum start time of the robot as the starting processing time of the current process, adding the known robot processing time of the process as the finishing time of the current process, wherein the available time of a robot worker is the idle starting time of the robot for finishing other processes, and the minimum start time is the last finishing time of the next process;

When the man-machine cooperative processing is performed, taking the maximum value of the available time of a worker, the available time of a robot and the minimum starting time as the starting processing time of the current working procedure, adding the man-machine cooperative processing time of the known working procedure, and taking the maximum value as the finishing time of the current working procedure;

Then selecting the minimum value of the finishing time of the three processing modes, and taking the corresponding processing mode as the processing mode of the current working procedure, and simultaneously obtaining the finishing time of the current working procedure, namely the working position time after the working procedure is distributed to the current working position;

an initial list of process recipe is generated based on the recipe of all the processes.

Optionally, the step S3 specifically includes:

S31, initializing continuous unmodified iteration times and accumulated unmodified times to be 0, and enabling a tabu table to be empty;

s32, assigning the initial solutions of the three sub-problems to a current solution;

s33, transforming the current solution according to the designed neighborhood action to generate a neighborhood solution, if the neighborhood solution is superior to the current solution, assigning the neighborhood solution to the current solution, zeroing the continuous unmodified iteration times, otherwise adding one to the continuous unmodified iteration times and the accumulated unmodified times, and executing a disturbance program;

s34, when the number of times of accumulated non-improvement reaches the set parameter D1, starting a restarting program, re-executing an initial solution generating process, generating a new initial solution, and repeating the process;

and S35, when the number of continuous and unmodified iterations reaches the set parameter D2, a stopping criterion is met, and the program is ended.

Optionally, the perturbation procedure is:

Using ST _max and ST _min to respectively represent the maximum and minimum station time, and Task _max and Task _min to respectively represent the procedure set on the station corresponding to the maximum and minimum station time, if the robot is not allocated on the station with the maximum station time and the robot is allocated on the station with the minimum station time, moving the robot to the station with the maximum station time;

Or alternatively

One procedure is randomly selected from the Task _max, and one position is randomly selected from the Task _min to insert the selected procedure under the premise of meeting the procedure priority relation.

In another aspect, there is provided a parallel assembly line scheduling apparatus considering a complex human-machine cooperation mode, the apparatus comprising:

The decomposition module is used for establishing and analyzing a mixed integer programming model of the parallel assembly line balance problem PALBP-HRC considering the complex man-machine cooperation mode, and decomposing the PALBP-HRC into three sub-problems: a process allocation sub-problem, a robot allocation sub-problem and an intra-station resource scheduling sub-problem;

the initial solution generating module is used for randomly creating a procedure priority list and a robot list, performing procedure distribution, generating an initial procedure distribution list and a procedure processing mode list, respectively serving as initial solutions of procedure distribution sub-problems and in-station resource scheduling sub-problems, and taking the randomly generated robot list as the initial solution of the robot distribution sub-problems;

And the iterative optimization module is used for carrying out iterative optimization on the initial solutions of the three sub-problems based on the improved tabu search algorithm framework to obtain an optimal scheme.

In another aspect, an electronic device is provided that includes a processor and a memory having instructions stored therein that are loaded and executed by the processor to implement the parallel assembly line scheduling method described above that takes into account a complex human-machine collaboration mode.

In another aspect, a computer readable storage medium having instructions stored therein that are loaded and executed by a processor to implement the parallel assembly line scheduling method described above that takes into account complex human-machine collaboration patterns is provided.

Compared with the prior art, the technical scheme has at least the following beneficial effects:

the invention can realize the efficient solution of PALBP-HRC and is beneficial to filling the blank in the current field.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a parallel assembly line scheduling method considering a complex man-machine cooperation mode according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a conventional parallel assembly line balancing problem PALBP;

FIG. 3 is a schematic diagram of a parallel assembly line balancing problem PALBP-HRC considering a complex human-machine collaboration model according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of different encoding and decoding modes of PALBP-HRC according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of two cases for solving the lower bound of takt time according to an embodiment of the present invention;

FIG. 6 is a block diagram of a parallel assembly line scheduling apparatus considering a complex human-machine cooperation mode according to an embodiment of the present invention;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention fall within the protection scope of the present invention.

As shown in fig. 1, an embodiment of the present invention provides a parallel assembly line scheduling method considering a complex man-machine cooperation mode, where the method includes:

S1, establishing and analyzing a mixed integer programming model of a parallel assembly line balance problem PALBP-HRC considering a complex man-machine cooperation mode, and decomposing the PALBP-HRC into three sub-problems: a process allocation sub-problem, a robot allocation sub-problem and a station internal resource scheduling (process processing mode selection) sub-problem;

The conventional parallel assembly line balancing problem PALBP, as shown in fig. 2, is composed of more than one line (two lines are taken as an example in the embodiment of the present invention), a series of horizontally placed stations are arranged on each assembly line, the working procedure of the product sequentially passes through each station, and only one worker working procedure is arranged on each station, so in the conventional parallel assembly line scheduling problem, only the working procedure needs to be distributed to each station, that is, only the decision exists.

Considering the parallel assembly line balancing problem PALBP-HRC of the complex man-machine cooperation mode, as shown in fig. 3, there is more than one line (especially two or three lines, two lines are taken as an example in the embodiment of the present invention) placed in parallel with each other, the design of the parallel assembly line with the cooperation robot combines the flexibility of parallel lines with the efficiency of man-machine cooperation, both the worker and the robot have various skills, so that they can execute the processes on different lines, at the same time, the processes of different products of the same model are distributed to two assembly lines, and the multi-line stations (the workers or robots on the stations can complete the processes on the two lines) between two adjacent assembly lines are distributed to each station in different combination modes, thereby improving the probability of load balancing distribution and further compressing the takt time. Known items of the embodiment of the invention are: the priority relation among the working procedures (for example, the working procedure 3 can be processed after the working procedures 1 and 2 are finished), the processing time of each processing mode of the working procedure and the number of stations, the time required for the robot to independently finish the same working procedure is 2 times of that of a worker, and the processing time of man-machine cooperation is 0.7 time of that of the worker. The worker and the robot can cooperate to complete the same working procedure, and can execute different working procedures in parallel, so that two assembly resources of the worker and the robot can be utilized to the maximum extent. The optimization objective of the embodiment of the invention is to minimize the takt time (maximum station time) of the parallel assembly line, and the parallel assembly line scheduling method considering the complex man-machine cooperation mode provided by the embodiment of the invention is described in detail below, and the method comprises the following steps:

The embodiment of the invention abstracts the problem into a mathematical model, and establishes a mixed integer programming model by combining a mixed integer programming technology, as follows:

index:

i, j Process index, i, j ε {1,2, …, NT }

H Assembly line index, H ε {1, …, H }

K-bit index, k ε {1,2, …, NS }

P-processing mode index, p.epsilon { p _H,p_R,p_C }

Parameters:

I set of procedures on all assembly lines, I= { I ₁,…,I_h }

Procedure set on I _h assembly line h

Number of processes on NT _h assembly line h

K set of stations, K= {1,2, …, NS }

Q number of robots

P set of processing modes, P= { P _H,p_R,p_C }

M is a very large positive number

Time for process i on line h of t _hip to be processed by processing means p

Direct set of preferential relationships between processes on line h of E _h

The variables:

CT beat time

Start time of step i s _i

U _hk binary variable, if station k on line h is used, then the value is 1

And (3) model:

Minimize CT (1)

The embodiment of the invention finds that the mixed integer programming model can be directly solved by using a commercial solver for small-scale examples, but the mixed integer programming model can be directly solved for medium-scale and large-scale examples, so that the speed is very slow, and even the solving result is difficult to obtain, therefore, the embodiment of the invention decomposes the PALBP-HRC into three sub-problems for the medium-scale and large-scale examples: the method comprises the steps of respectively solving an initial solution of three sub-problems, namely a process allocation sub-problem, a robot allocation sub-problem and an intra-station resource scheduling sub-problem, and performing iterative optimization on the initial solutions of the three sub-problems based on an improved tabu search algorithm framework to obtain an optimal scheme.

The efficient encoding and decoding process is very important, and the embodiment of the present invention designs three initial solution generating schemes and corresponding encoding and decoding methods thereof, as shown in fig. 4, where the first encoding and decoding method is as follows:

For the processes on two lines of parallel assembly lines, respectively creating separate priority lists randomly, respectively calculating the lower bound of the beat time of the two lines as the initial beat time of the two lines, respectively, wherein the initial unassigned process list is all the processes, and assigning the processes according to the priority lists of the two lines and the randomly created robot list (the Priority List (PL) describes the priority of each process, each element in the list is a value between 1 and the total number of the processes, a higher value represents the higher priority and is preferentially assigned to a station; the Robot List (RL) represents the assignment condition of a robot at each station, the value is 0 or 1, wherein 1 represents that the robot is assigned to the current station, and 0 represents that no robot), assigning the processes are performed by using the following method, and decoding to obtain the beat time:

Starting the distribution process from the first station, firstly distributing the processes on the first line to the stations according to the priority list of the first line and the initial beat time of the first line, sequencing the processes according to the descending order of the priority, judging whether all the previous processes with the highest priority are distributed, if all the previous processes are distributed completely, and calculating the station time after the process is distributed to the current station within the initial beat time of the first line by adopting an approximation method: adding the processing time of workers of each process on the first line (because only the processes on the two lines are uniformly distributed on each station, but calculating accurate station time is time-consuming, the processing modes of the processes are unified into workers, namely, the processing time of the process at the moment only needs to add the processing time of the workers of each process on the first line and is the same when calculating a process distribution list of the second line), then distributing the process to the current station, removing the process from the unassigned process list, otherwise, skipping the process, and distributing the next process arranged in descending order of priority;

The second encoding and decoding mode is as follows:

Merging all working procedures on two lines of the parallel assembly line, randomly creating a priority list, wherein the priority value range of the priority list is from 1 to the total number of the working procedures of the two lines, the working procedure number of the second line is followed by the first line, and calculating the lower bound of the takt time after the working procedures on the two lines are summarized as initial takt time;

The third encoding and decoding mode is as follows:

Solving the corresponding parallel assembly line balance problem PALBP (a mixed integer programming model of PALBP can be established, a commercial solver is used for solving, the specific solving mode is the prior art, and details are not repeated here), distributing the obtained working procedures in the optimal solution, converting the working procedures into a priority list, and calculating the lower bound of takt time after the working procedures on two lines of the parallel assembly line are summarized as initial takt time;

The embodiment of the invention can respectively take the initial process allocation lists generated by the three coding and decoding modes as the initial solutions of the process allocation sub-processes, and can take the optimal (minimum beat time) initial process allocation list generated by the three coding and decoding modes as the initial solution of the process allocation sub-processes, and the embodiment of the invention is not limited and is within the protection scope of the embodiment of the invention.

The calculating the lower bound of the takt time of the two lines or the lower bound of the takt time after the process is summarized on the two lines specifically comprises the following steps:

As shown in fig. 5, in the first case, t ₁ is smaller than t ₂, in order to reduce the total processing time, some processes are transferred from robotic processing to worker processing:

The calculation method of the lower bound of the final beat time is as follows:

Calculating the station time by adopting an accurate method, which comprises the following steps:

After the robots are introduced, the assembly line stations are divided into two types, one type is free of the robots, and only workers can assemble resources in the stations; the second category is that robots exist, in such stations, there are two kinds of assembly resources, human and robot, thereby creating a problem of scheduling resources in the stations. The resource scheduling problem is that the worker resources are occupied by adopting a manual processing mode, namely, the worker can only process one working procedure at the same time. Similarly, robot processing occupies robot resources. In the man-machine cooperation mode, a person and a robot jointly execute the same procedure, namely, the mode occupies two assembly resources at the same time. Different from a station without a robot, the robot and the robot in the station can execute different working procedures simultaneously, namely, the working time of the robot and the station generates a superposition part, so that the station time cannot be calculated by using the sum of all working procedure times.

Optionally, the step S3 specifically includes:

s33, transforming the current solution according to the designed neighborhood action to generate a neighborhood solution, if the neighborhood solution is superior to the current solution (the beat time is smaller than that of the current solution), assigning the neighborhood solution to the current solution, zeroing the continuous unmodified iteration times, otherwise adding one to the continuous unmodified iteration times and the accumulated unmodified times, and executing a disturbance program;

Optionally, the perturbation procedure is:

Or alternatively

As shown in fig. 6, the embodiment of the present invention further provides a parallel assembly line scheduling apparatus considering a complex man-machine cooperation mode, where the apparatus includes:

The decomposition module 610 is configured to build and analyze a mixed integer programming model of parallel assembly line balance problem PALBP-HRC considering a complex human-computer collaboration mode, and decompose the PALBP-HRC into three sub-problems: a process allocation sub-problem, a robot allocation sub-problem and an intra-station resource scheduling sub-problem;

An initial solution generating module 620, configured to randomly create a process priority list and a robot list, perform process allocation, generate an initial process allocation list and a process processing mode list, respectively serve as initial solutions of a process allocation sub-problem and an intra-station resource scheduling sub-problem, and use the randomly generated robot list as an initial solution of a robot allocation sub-problem;

The iterative optimization module 630 is configured to perform iterative optimization on the initial solutions of the three sub-problems based on the improved tabu search algorithm framework, so as to obtain an optimal solution.

The functional structure of the parallel assembly line scheduling device considering the complex man-machine cooperation mode provided by the embodiment of the invention corresponds to the parallel assembly line scheduling method considering the complex man-machine cooperation mode provided by the embodiment of the invention, and is not repeated herein.

Fig. 7 is a schematic structural diagram of an electronic device 700 according to an embodiment of the present invention, where the electronic device 700 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 701 and one or more memories 702, where the memories 702 store instructions, and the instructions are loaded and executed by the processors 701 to implement the steps of the parallel assembly line scheduling method that consider the complex man-machine cooperation mode.

In an exemplary embodiment, a computer readable storage medium, such as a memory comprising instructions executable by a processor in a terminal to perform the parallel assembly line scheduling method described above that takes into account the complex human-machine collaboration mode, is also provided. For example, the computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.

Claims

1. A parallel assembly line scheduling method considering a complex human-machine cooperation mode, the method comprising:

s3, based on an improved tabu search algorithm framework, carrying out iterative optimization on initial solutions of three sub-problems to obtain an optimal scheme;

And S2, randomly creating a procedure priority list and a robot list, performing procedure allocation, and generating an initial procedure allocation list, wherein the method specifically comprises the following steps of:

summarizing an initial first-line process distribution list and an initial second-line process distribution list to obtain an initial parallel assembly line process distribution list, wherein the initial parallel assembly line process distribution list comprises initial distribution conditions and processing sequences of processes on all stations, and calculating station time of all stations by adopting an accurate method in combination with a robot distribution list, wherein the maximum station time is takt time obtained by decoding;

The step S3 specifically comprises the following steps:

2. The method of claim 1, wherein the mixed integer programming model is as follows: index:

i, j Process index, i, j ε {1,2, …, NT }

H Assembly line index, H ε {1, …, H }

K-bit index, k ε {1,2, …, NS }

P-processing mode index, p.epsilon { p _H,p_R,p_C }

Parameters:

i set of procedures on all assembly lines, I= { I ₁,...,I_h }

Procedure set on I _h assembly line h

Number of processes on NT _h assembly line h

K set of stations, k= {1,2,..

Q number of robots

P set of processing modes, P= { P _H,p_R,p_C }

M is a very large positive number

Time for process i on line h of t _hip to be processed by processing means p

Direct set of preferential relationships between processes on line h of E _h

The variables:

CT beat time

Start time of step i s _i

U _hk binary variable, if station k on line h is used, then the value is 1

And (3) model:

Minimize CT (1)

3. The method according to claim 1, wherein the step S2 is to randomly create a step priority list and a robot list, perform step assignment, and generate an initial step assignment list, and specifically includes:

4. The method according to claim 1, wherein the step S2 is to randomly create a step priority list and a robot list, perform step assignment, and generate an initial step assignment list, and specifically includes:

5. The method according to claim 1, 3 or 4, characterized in that the lower bound of the takt time of the two lines is calculated separately or after the process summary on the two lines is calculated, in particular comprising:

The calculation method of the lower bound of the final beat time is as follows:

6. The method according to claim 1, 3 or 4, wherein the station time is calculated by an accurate method, comprising:

when the robot processes, taking the maximum value of the available time and the minimum start time of the robot as the starting processing time of the current process, adding the known processing time of the robot of the process as the finishing time of the current process, wherein the available time of the robot is the idle starting time of the robot for finishing other processes, and the minimum start time is the last finishing time of the next process;

7. The method of claim 1, wherein the perturbation program is:

Or alternatively

8. Parallel assembly line scheduling apparatus taking into account complex human-machine cooperation patterns, performing the parallel assembly line scheduling method of any one of claims 1-7, characterized in that the apparatus comprises: