CN111985700A - Vehicle carrying single quantity balancing method and device for determining home delivery and loading - Google Patents
Vehicle carrying single quantity balancing method and device for determining home delivery and loading Download PDFInfo
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Abstract
The embodiment of the invention provides a vehicle carrying single quantity balancing method and device for determining home delivery, wherein the method comprises the following steps: acquiring vehicle information of a vehicle to be distributed and order information of an order to be distributed; performing iterative exchange distribution of orders on the vehicles to be distributed to obtain a distribution scheme which enables a preset objective function to be minimum as a candidate distribution scheme; adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme. Compared with manual cable arranging, the balance of carrying single quantity and service charge among vehicles is considered in the cable arranging process in a quantitative mode, the cable arranging efficiency is obviously improved, meanwhile, the requirement of scheduling personnel on balance is met, and the problem that the acceptance of certain line carrying single quantity and service charge on lines is reduced due to too low or too high line carrying single quantity and service charge on the line groups is avoided.
Description
Technical Field
The invention relates to the field of home delivery and loading, in particular to a vehicle carrying single quantity balancing method and device for determining home delivery and loading.
Background
The home delivery service is a typical route planning scene, and has the general characteristics of a plurality of Vehicle Routing Problems (VRP), such as the minimum number of vehicles and the shortest route mileage on the premise that optimization targets meet the requirements of constraints. At the same time, many common constraints such as lift-off time windows, vehicle capacity, maximum travel distance, loaded goods type limitations, etc. need to be considered. In addition to these common characteristics, the home delivery and loading scene also has many demands which are not available in other services, such as restriction of different types of goods loading, limitation of carrying single quantity in time period all day, balancing of carrying single quantity between different vehicles and the like due to installation capability of vehicle group personnel. These requirements will undoubtedly increase the complexity of the line planning, increase the cost of the wire arrangement and reduce the efficiency of the wire arrangement, which also puts new demands on the line planning algorithm.
This need for vehicle load balancing arises from considerations of crew workload and revenue levels during service execution. The proficiency and the working efficiency of the distribution and installation service are different among the vehicle groups, and the quantity of tasks which can be completed every day is different, so that the route planning needs to ensure that the vehicle groups can complete the distributed tasks on time. At the same time, there must not be excessive differences in workload and income levels between consist groups with close capacity in order to improve line acceptance by consist personnel. In the manual cable arrangement mode, the scheduling personnel can respectively evaluate the workload and service charge of each order, the working efficiency of the vehicle group personnel and other factors, and meanwhile, all other cable arrangement related constraints need to be considered, and the order is distributed to each vehicle group in a short time.
In the process of manual wire arrangement, the dispatcher needs to consider various wire arrangement constraints including vehicle carrying single quantity balance. They often line their orders using experience-based logic and rules, such as first ordering an order for a particular region or type. However, these logic and rules rely on the personal experience of the dispatchers, and different dispatchers often have differences in the criteria for equalization, and the same order may be placed on disparate lines. Secondly, the manual wire arrangement method lacks quantitative indexes, so that various line requirements including vehicle carrying single quantity balance cannot be accurately controlled. In addition, the complexity of the line planning problem increases exponentially with the increase of the number of orders, and when the service scale expands or a large number of orders are suddenly happened, the time consumption of manual cable arrangement increases greatly and the cable arrangement quality cannot be guaranteed.
Disclosure of Invention
In order to solve the above problems, embodiments of the present invention provide a vehicle carrying single quantity balancing method and apparatus for determining home delivery.
In a first aspect, an embodiment of the present invention provides a vehicle carrying list balancing method for determining home delivery, including: acquiring vehicle information of a vehicle to be distributed and order information of an order to be distributed; performing iterative exchange distribution of orders on the vehicles to be distributed to obtain a distribution scheme which enables a preset objective function to be minimum as a candidate distribution scheme; adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme; the penalty item is determined according to a penalty coefficient and service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
Further, before the iterative exchange allocation of the order to the vehicle to be allocated, the method further includes: and determining the objective function according to the total mileage of all vehicles, the carrying rate of the vehicles, the order distribution rate and the corresponding weight coefficient.
Further, the obtaining of the allocation scheme that minimizes the objective function includes: and acquiring a distribution scheme for minimizing the target function based on a large-scale neighborhood search algorithm.
Further, after the vehicle information of the vehicle to be allocated and the order information of the order to be allocated are obtained, the method further includes: according to the total order quantity of the order to be distributed, determining the average carrying order quantity and the average service fee of each vehicle, combining the corresponding preset proportion, determining the upper limit of the carrying order quantity and the upper limit of the service fee of each vehicle, and correspondingly: and in the iterative distribution process of each scheme, the carrying unit quantity and the service charge of each vehicle are not more than the upper limit value.
Further, after the vehicle information of the vehicle to be allocated and the order information of the order to be allocated are obtained, the method further includes: and determining the lower limit of the carrying order quantity and the lower limit of the service fee of each vehicle according to the total order quantity of the order to be distributed and the corresponding preset proportion.
Further, the penalty factor is incremented with the number of allocations.
Further, after obtaining the target allocation scheme, the method further includes: if the lines with the carrying order quantity lower than the carrying order quantity lower limit or the service fee lower than the service fee lower limit are detected, the unallocated orders or other line orders are adjusted to the lines with the carrying order quantity lower than the carrying order quantity lower limit or the service fee lower than the service fee lower limit in the preset distance range.
In a second aspect, an embodiment of the present invention provides a vehicle carrying list balancing apparatus for determining home delivery, including: the acquisition module is used for acquiring vehicle information of the vehicle to be distributed and order information of the order to be distributed; the pre-allocation module is used for performing iterative exchange allocation of orders on the vehicles to be allocated to obtain an allocation scheme which enables the objective function to be minimum and is used as a candidate allocation scheme; the redistribution module is used for adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme; the penalty item is determined according to a penalty coefficient and service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method for determining the vehicle-borne single quantity balance of home delivery in the first aspect of the present invention.
In a fourth aspect, embodiments of the present invention provide a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implementing the steps of the method for determining vehicle-borne order balance of home delivery in the first aspect of the present invention.
According to the vehicle carrying single quantity balancing method and device for determining home delivery and loading, penalty items are added to the objective function to serve as a new objective function, iterative exchange distribution of orders is conducted on vehicles to be distributed, and a distribution scheme enabling the new objective function to be minimum is obtained and serves as a target distribution scheme. Compared with manual cable arranging, the balance of carrying single quantity and service charge among vehicles is considered in the cable arranging process in a quantitative mode, the cable arranging efficiency is obviously improved, meanwhile, the requirement of scheduling personnel on balance is met, and the problem that the acceptance of certain line carrying single quantity and service charge on lines is reduced due to too low or too high line carrying single quantity and service charge on the line groups is avoided. Compared with the traditional wire arranging algorithm based on integer programming or heuristic algorithm, the method can quickly iterate and output the line meeting the service requirements including vehicle carrying single quantity balance in reasonable calculation time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flowchart of a vehicle load balancing method for determining home delivery according to an embodiment of the present invention;
FIG. 2 is a structural diagram of a vehicle load sheet balancing device for determining home delivery according to an embodiment of the present invention;
fig. 3 is a schematic physical structure 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 clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Common VRP algorithms are typically based on mixed integer programming or heuristic algorithms. The former has a large calculation amount, and usually requires a long solution time, and if the factor of vehicle carrying single quantity balance is considered, the calculation time is further prolonged, and even a feasible solution may not be found. Although a common heuristic algorithm can conveniently take the factors of vehicle carrying single quantity balance into consideration, due to the limitations of operator and exchange logic design, for a large-scale actual service scene, the search process is easy to fall into local optimum, and even a feasible solution meeting the balance requirement and in service cannot be provided.
Fig. 1 is a flowchart of a vehicle carrying single quantity balancing method for determining home delivery and loading according to an embodiment of the present invention, and as shown in fig. 1, a vehicle carrying single quantity balancing method for determining home delivery and loading according to an embodiment of the present invention includes:
101. vehicle information of the vehicle to be distributed and order information of the order to be distributed are obtained.
First, order information of all orders to be distributed is obtained, wherein the order information is information customized by a receiver according to a receiving address, receiving time, required cargo quantity and the like. In the embodiment of the invention, the order information comprises a receiving place, receiving time and service charge, and also can comprise the cargo quantity. The cargo amount may specifically be cargo weight, cargo quantity, cargo volume. Meanwhile, vehicle information for scheduling needs to be acquired, and the vehicle information can comprise the number of vehicles, the types of the vehicles and the working efficiency of a corresponding vehicle group.
102. And performing iterative exchange distribution of orders on the vehicles to be distributed to obtain a distribution scheme which enables a preset objective function to be minimum as a candidate distribution scheme.
Each vehicle delivers the goods of at least one receiving station, but in order to improve delivery efficiency, generally, each vehicle delivers the goods required for a plurality of receiving stations, that is, a certain amount of goods is unloaded at different receiving stations during transportation. Because of the presence of multiple stations, a more optimal delivery path is required to reduce costs, and because of the greater number of delivery vehicles, each vehicle is also scheduled on a more optimal delivery path and allocated a reasonable amount of cargo.
In the initial order distribution scheme, a plurality of orders can be distributed to a plurality of delivery vehicles according to the distribution of the orders in time from early to late and from inside to outside in space, so as to obtain the initial order distribution scheme. Then, any two orders are subjected to iterative exchange to obtain a new distribution scheme. And after a new distribution scheme is obtained each time, evaluating the rationality of the order distribution scheme according to the objective function. If the new allocation scheme makes the objective function value smaller, the new allocation scheme is retained. Finally, the allocation that minimizes the objective function is obtained as a candidate allocation for further processing at 103. The objective function is determined according to an optimization objective, and the optimization objective can be set according to specific requirements, for example, the optimization objective is that the total transportation mileage of all vehicles is shortest, the average arrival time is minimum, and the like. In an alternative embodiment of the present invention, the optimization goals are high order distribution, shortest total haul mileage, and highest vehicle carrying rate.
103. Adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme.
The problems of carrying order quantity balance and service fee balance of each vehicle are considered, namely the balance of the number of orders carried by each vehicle (or the cargo quantity of the orders) and the balance of the total service fee obtained after each vehicle is sent for service. In the embodiment of the invention, the lower limit value of the carrying single quantity and the lower limit value of the total service fee are predetermined before distribution, and then the line is adjusted by taking the lower limit value and the total service fee as a target, so that all vehicles can meet the requirements of the minimum carrying single quantity and the minimum service fee as far as possible. Specifically, the current carrying list amount is the carrying list amount of the vehicle after the iterative allocation, and the current total service fee is the total service fee of the order allocated by the vehicle after the iterative allocation.
In 103, multiplying one or two of the difference between the current carrying unit quantity and the lower limit of the carrying unit quantity and the difference between the current total service charge and the lower limit of the service charge by corresponding penalty coefficients to obtain penalty terms, adding the penalty terms into the original objective function to obtain a new objective function, and performing further optimization. Taking the difference between the service volume and the current carrying unit volume as an example, the penalty term is as follows:
wherein, is a penalty factor,/kIs the current carrying capacity of k cars,/lIs the lower limit of the carrying unit of the vehicle. Correspondingly, the difference between the current total service charge and the lower limit of the service charge can also be added into the penalty item.
Any two orders are exchanged to obtain a new allocation scheme, and then the new allocation scheme is evaluated by a new objective function, and if the objective function value becomes small, the new allocation scheme is reserved. The final allocation scheme will move orders from lines with large carrier volumes and total service charges to lines that do not meet the requirements. And judging whether all the flat cable constraints are met or not and reducing the objective function value through the new objective function. And if the order meets the requirement, moving the order, otherwise, continuously iterating, and converging the final result in the direction of more balanced carrying list quantity, so that the obtained target distribution scheme can meet the balance of the carrying list quantity and the balance of the service fee.
According to the vehicle carrying single quantity balancing method for determining home delivery and loading, the penalty item is added to the target function to serve as a new target function, iterative exchange distribution of orders is conducted on the vehicles to be distributed, and a distribution scheme enabling the new target function to be the minimum is obtained and serves as a target distribution scheme. Compared with manual cable arranging, the balance of carrying single quantity and service charge among vehicles is considered in the cable arranging process in a quantitative mode, the cable arranging efficiency is obviously improved, meanwhile, the requirement of scheduling personnel on balance is met, and the problem that the acceptance of certain line carrying single quantity and service charge on lines is reduced due to too low or too high line carrying single quantity and service charge on the line groups is avoided. Compared with the traditional wire arranging algorithm based on integer programming or heuristic algorithm, the method can quickly iterate and output the line meeting the service requirements including vehicle carrying single quantity balance in reasonable calculation time.
Based on the content of the foregoing embodiment, as an optional embodiment, before the order distribution is performed on the vehicle to be distributed, the method further includes: and determining an objective function according to the total mileage of all vehicles, the carrying rate of the vehicles, the order distribution rate and the corresponding weight coefficient.
The higher the carrying rate of the vehicle, the fewer the number of vehicles used, so that the cost can be reduced. For the order allocation rate, the more orders are allocated, and the fewer the unallocated orders are, the lower the cost caused by the unallocated orders are (for example, the unallocated orders need to occupy a warehouse, the probability of repurchase of a user is reduced, and the like). The objective function may be inversely related to the carrying rate of the vehicle and the order distribution rate.
According to the method and the device, the objective function is determined according to the total mileage of all vehicles, the carrying rate of the vehicles, the order distribution rate and the corresponding weight coefficients, and the obtained candidate distribution scheme can be guaranteed to meet the wire arrangement constraint, so that the wire arrangement constraint is met as far as possible while the final target distribution scheme meets the balance.
Based on the content of the foregoing embodiment, as an optional embodiment, before the order distribution is performed on the vehicle to be distributed, the method further includes: and determining an objective function according to the total mileage of all vehicles, the fixed cost of the vehicles, the unallocated cost of the order and the corresponding weight coefficient.
The fixed cost of the vehicle refers to the cost brought by using the vehicle, and the unallocated order refers to the cost brought by the unallocated order, which can be quantified according to specific situations.
The embodiment of the present invention determines the objective function according to the total mileage of all vehicles, the fixed cost of the vehicles, the unallocated order cost and the corresponding weight coefficient, which is not specifically limited, and includes but is not limited to the following objective functions:
where K is the set of all vehicles, A is the set of edges formed by all order sites, and P is the set of all orders. dijDistance of side i → j, xijkThe value is 1 or 0, which represents whether the vehicle k passes through the edge i → j, vkFor a fixed cost of the vehicle k, ziIs the unallocated cost for order i. Alpha, beta and gamma are weight coefficients respectively, and are used for adjusting the weight of each cost. According to the method and the device, the objective function is determined according to the total mileage of all vehicles, the fixed cost of the vehicles, the unallocated order cost and the corresponding weight coefficient, and the obtained candidate distribution scheme can be guaranteed to meet the winding displacement constraint, so that the final target distribution scheme meets the balance and meets the winding displacement constraint as far as possible.
Based on the content of the foregoing embodiment, as an optional embodiment, the obtaining of the candidate allocation scheme that minimizes the preset objective function includes: based on a large-scale neighborhood search algorithm, a distribution scheme for minimizing the objective function is obtained.
The domain search algorithm is an improved algorithm with wide application, in the neighborhood search, the larger the domain is, the better the quality of the domain solution is, so that the quality of the final solution is better, but the longer the domain search time is. The large-scale domain search algorithm is an effective search strategy, so that the optimization capability of a large-scale neighborhood can be maintained, the defects of low efficiency and time consumption can be overcome, and the competitiveness of the algorithm is improved.
Based on the content of the foregoing embodiment, as an optional embodiment, after obtaining the vehicle information of the vehicle to be allocated and the order information of the order to be allocated, the method further includes: according to the total order quantity of the order to be distributed, determining the average carrying order quantity and the average service fee of each vehicle, combining the corresponding preset proportion, determining the upper limit of the carrying order quantity and the upper limit of the service fee of each vehicle, and correspondingly: and in the iterative distribution process of each scheme, the carrying unit quantity and the service charge of each vehicle are not more than the upper limit value.
And evaluating the total unit quantity to be distributed on the day and available vehicle resources, and respectively configuring the upper limit of the vehicle carrying unit quantity and the upper limit of the service fee of each vehicle group, wherein the upper limit of the vehicle carrying unit quantity and the upper limit of the service fee are used as basic constraints of algorithm cable arrangement, and the carrying unit quantity and the total service fee of each vehicle are ensured not to exceed the upper limits in the cable arrangement process. Specifically, the average order amount and service fee to each vehicle are calculated according to the order amount and available vehicle resources on the current day, and the upper limit of the carrying order amount and the upper limit of the service fee of each vehicle are obtained by adjusting according to a preset proportion so as to meet the order amount on the current day. The preset proportion here refers to a scaling proportion of the upper limit of the carrying unit quantity and the upper limit of the service fee, and different preset proportions may be set for the carrying unit quantity and the service fee, respectively, or may be set to be the same.
Further, if the upper limit of the carrying single quantity or the upper limit of the service fee is larger than a preset upper limit default value of the carrying single quantity or a preset upper limit default value of the service fee, the upper limit default value of the carrying single quantity or the upper limit default value of the service fee is used as the upper limit of the carrying single quantity and the upper limit of the service fee in the iterative allocation process of each scheme.
In consideration of the limitation of the vehicle loading capacity, a default value of the upper limit of the carrying order quantity or a default value of the upper limit of the service fee can be set in advance, and if the daily ordered amount is too large, the carrying order quantity and the service fee are not suitable to be distributed to the existing vehicles. That is, if the upper limit of the carrying unit amount or the upper limit of the service fee obtained from the total unit amount on the day is larger than the default value, the default value is still used as the limiting condition in the distribution process.
Further, determining the upper limit of the carrying list amount and the upper limit of the service fee of each vehicle by combining the corresponding preset proportion comprises the following steps: and determining the upper limit of the carrying list amount and the upper limit of the service fee of each vehicle by combining the corresponding preset proportion according to the carrying efficiency of each vehicle.
Considering that the train carrying efficiency of different vehicles is different, the carrying list upper limit and the service charge upper limit are different based on different carrying efficiencies, and the carrying efficiency can be set by a dispatcher according to the working capacity of the train. And dynamically setting the upper limit of the carrying order quantity and the upper limit of the service expense according to the total order quantity to be distributed and the carrying efficiency, and under the condition that the fluctuation of the total order quantity and the number of available vehicles is large, the constraint of the distribution process is favorably and reasonably configured, so that the distribution result is reasonable. Specifically, the upper limit of the carrying list amount and the upper limit of the service fee of each vehicle are obtained by combining the quantitative determination of the carrying efficiency of the vehicle on the basis of the preset proportion of the carrying list amount and the service fee.
Based on the content of the foregoing embodiment, as an optional embodiment, after obtaining the vehicle information of the vehicle to be allocated and the order information of the order to be allocated, the method further includes: and determining the lower limit of the carrying order quantity and the lower limit of the service fee of each vehicle according to the total order quantity of the order to be distributed and the corresponding preset proportion.
And determining the lower limits of the carrying orders and the service fees of all the vehicle groups, aiming at the lower limits, adjusting the route in 103, and ensuring that all the vehicles can meet the requirements of the minimum carrying orders and the service fees as much as possible so as to realize the balance of the carrying orders and the service fees. Different lower limits of carrying orders and service fees are needed to be set when the total orders to be distributed are different. Specifically, the average amount of the orders and the average service fee to each vehicle are calculated according to the amount of the orders and the available vehicle resources on the current day, and the lower limit of the carrying amount of each vehicle and the lower limit of the service fee are obtained by adjusting according to a preset proportion so as to meet the amount of the orders on the current day. The preset proportion here refers to a scaling proportion of the lower limit of the carrying unit quantity and the lower limit of the service fee, and different preset proportions may be set for the carrying unit quantity and the service fee respectively, or may be set to be the same.
Further, if the lower limit of the carrying order quantity or the lower limit of the service fee is smaller than a preset lower limit default of the carrying order quantity or the preset lower limit default of the service fee, the lower limit default of the carrying order quantity or the lower limit default of the service fee is used as the lower limit of the carrying order quantity and the lower limit of the service fee in the penalty item.
In consideration of the situation that the total unit amount is small and the number of available vehicles is too large, a carrying unit amount lower limit default value or a service fee lower limit default value can be preset. And if the lower limit of the carrying order quantity or the lower limit of the service fee obtained according to the total order quantity on the current day is smaller than the default value, the default value is used as the lower limit value in the distribution process, so that the problem that the total order quantity on the current day is less and enough orders cannot be distributed to the existing vehicles is solved.
Based on the content of the above embodiment, as an alternative embodiment, the penalty coefficient is increased with the number of iterations. Similar to the penalty function in the simulated annealing calculation, the value of the penalty coefficient is continuously increased through each iteration, which is equivalent to increasing the weight of the balance factor in the overall objective function of the line, so that the line gradually converges to the balance target, thereby being beneficial to obtaining a line distribution scheme meeting the balance of carrying single quantity and service charge and avoiding the influence of the weights of other optimization targets.
Based on the content of the foregoing embodiment, as an optional embodiment, after obtaining the target allocation scheme, the method further includes: if the lines with the carrying order quantity lower than the carrying order quantity lower limit or the service fee lower than the service fee lower limit are detected, the unallocated orders or other line orders are adjusted to the lines with the carrying order quantity lower than the carrying order quantity lower limit or the service fee lower than the service fee lower limit in the preset distance range.
After the target distribution scheme is obtained, based on the line distribution result of the target distribution scheme, lines with low carrying order quantity and excessively high service cost are selected in a targeted mode to be adjusted, or unallocated orders are distributed to lines with low carrying order quantity and excessively low service cost. At this time, the constraint of the service partition may be relaxed appropriately, that is, the two lines to be adjusted may not be in one service partition, as long as the distance satisfies the preset distance range. The line balance can be further improved by moving lines with high order carrying capacity and service charges to lower lines for adjacent lines.
Fig. 2 is a structural diagram of a vehicle carrying list quantity balancing apparatus for determining home delivery and loading according to an embodiment of the present invention, and as shown in fig. 2, the vehicle carrying list quantity balancing apparatus for determining home delivery and loading includes: an acquisition module 201, a pre-allocation module 202 and a reallocation module 203. The obtaining module 201 is configured to obtain vehicle information of a vehicle to be allocated and order information of an order to be allocated; the pre-allocation module 202 is configured to perform iterative exchange allocation of orders for vehicles to be allocated, and acquire an allocation scheme that minimizes a preset objective function, as a candidate allocation scheme; the redistribution module 203 is used for adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme; the penalty item is determined according to the penalty coefficient and the service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
The device embodiment provided in the embodiments of the present invention is for implementing the above method embodiments, and for details of the process and the details, reference is made to the above method embodiments, which are not described herein again.
According to the vehicle carrying single quantity balancing device for determining home delivery and loading, the penalty item is added to the objective function to serve as a new objective function, iterative exchange distribution of orders is conducted on the vehicles to be distributed, and a distribution scheme enabling the new objective function to be the minimum is obtained to serve as a target distribution scheme. Compared with manual cable arranging, the balance of carrying single quantity and service charge among vehicles is considered in the cable arranging process in a quantitative mode, the cable arranging efficiency is obviously improved, meanwhile, the requirement of scheduling personnel on balance is met, and the problem that the acceptance of certain line carrying single quantity and service charge on lines is reduced due to too low or too high line carrying single quantity and service charge on the line groups is avoided. Compared with the traditional wire arranging algorithm based on integer programming or heuristic algorithm, the method can quickly iterate and output the line meeting the service requirements including vehicle carrying single quantity balance in reasonable calculation time.
Fig. 3 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 3, the electronic device may include: a processor (processor)301, a communication Interface (communication Interface)302, a memory (memory)303 and a bus 304, wherein the processor 301, the communication Interface 302 and the memory 303 complete communication with each other through the bus 304. The communication interface 302 may be used for information transfer of an electronic device. Processor 301 may call logic instructions in memory 303 to perform a method comprising: acquiring vehicle information of a vehicle to be distributed and order information of an order to be distributed; performing iterative exchange distribution of orders on the vehicles to be distributed to obtain a distribution scheme which enables a preset objective function to be minimum as a candidate distribution scheme; adding a penalty item to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme; the penalty item is determined according to the penalty coefficient and the service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
In addition, the logic instructions in the memory 303 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-described method embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, and for example, the method includes: acquiring vehicle information of a vehicle to be distributed and order information of an order to be distributed; performing iterative exchange distribution of orders on the vehicles to be distributed to obtain a distribution scheme which enables a preset objective function to be minimum as a candidate distribution scheme; adding a penalty item to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme; the penalty item is determined according to the penalty coefficient and the service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A vehicle carrying single quantity balancing method for determining home delivery is characterized by comprising the following steps:
acquiring vehicle information of a vehicle to be distributed and order information of an order to be distributed;
performing iterative exchange distribution of orders on the vehicles to be distributed to obtain a distribution scheme which enables a preset objective function to be minimum as a candidate distribution scheme;
adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme;
the penalty item is determined according to a penalty coefficient and service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
2. The vehicle waybill balancing method for determining home delivery according to claim 1, wherein before the iterative swap allocation of orders for vehicles to be allocated, further comprising:
and determining the objective function according to the total mileage of all vehicles, the carrying rate of the vehicles, the order distribution rate and the corresponding weight coefficient.
3. The vehicle on-board balance method for determining home delivery according to claim 1, wherein the obtaining of the allocation scheme that minimizes the objective function comprises:
and acquiring a distribution scheme for minimizing the target function based on a large-scale neighborhood search algorithm.
4. The vehicle carrying order quantity balancing method for determining home delivery according to claim 1, wherein after acquiring the vehicle information of the vehicle to be allocated and the order information of the order to be allocated, the method further comprises:
according to the total order quantity of the order to be distributed, determining the average carrying order quantity and the average service fee of each vehicle, combining the corresponding preset proportion, determining the upper limit of the carrying order quantity and the upper limit of the service fee of each vehicle, and correspondingly:
and in the iterative distribution process of each scheme, the carrying unit quantity and the service charge of each vehicle are not more than the upper limit value.
5. The vehicle carrying order quantity balancing method for determining home delivery according to claim 1, wherein after acquiring the vehicle information of the vehicle to be allocated and the order information of the order to be allocated, the method further comprises:
and determining the lower limit of the carrying order quantity and the lower limit of the service fee of each vehicle according to the total order quantity of the order to be distributed and the corresponding preset proportion.
6. The vehicle load balancing method for determining home delivery according to claim 1, wherein the penalty factor increases with the number of assignments.
7. The vehicle on-board balance method for determining home delivery according to claim 1, wherein after obtaining the target allocation plan, the method further comprises:
if the lines with the carrying order quantity lower than the carrying order quantity lower limit or the service fee lower than the service fee lower limit are detected, the unallocated orders or other line orders are adjusted to the lines with the carrying order quantity lower than the carrying order quantity lower limit or the service fee lower than the service fee lower limit in the preset distance range.
8. A vehicle load sheet equalization apparatus for determining home delivery, comprising:
the acquisition module is used for acquiring vehicle information of the vehicle to be distributed and order information of the order to be distributed;
the pre-allocation module is used for performing iterative exchange allocation of orders on the vehicles to be allocated to obtain an allocation scheme which enables the objective function to be minimum and is used as a candidate allocation scheme;
the redistribution module is used for adding a penalty term to the target function to serve as a new target function, performing iterative exchange distribution on orders of vehicles to be distributed, and acquiring a distribution scheme which enables the new target function to be minimum to serve as a target distribution scheme;
the penalty item is determined according to a penalty coefficient and service quantity difference values of all vehicles, and the service quantity difference values comprise the difference value of the current carrying single quantity and the lower limit of the carrying single quantity and/or the difference value of the current total service fee and the lower limit of the service fee.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for determining vehicle on-board unit load for home delivery according to any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the method for vehicle load balancing for determining home delivery according to any of claims 1 to 7.
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