The time dependent vehicle routing problem with time windows（TDVRPTW） is considered. A multi-type ant system（MTAS） algorithm hybridized with the ant colony system（ACS）and the max-min ant system（MMAS） algorithm...The time dependent vehicle routing problem with time windows（TDVRPTW） is considered. A multi-type ant system（MTAS） algorithm hybridized with the ant colony system（ACS）and the max-min ant system（MMAS） algorithms is proposed. This combination absorbs the merits of the two algorithms in solutions construction and optimization separately. In order to improve the efficiency of the insertion procedure, a nearest neighbor selection（NNS） mechanism, an insertion local search procedure and a local optimization procedure are specified in detail. And in order to find a balance between good scouting performance and fast convergence rate, an adaptive pheromone updating strategy is proposed in the MTAS. Computational results confirm the MTAS algorithm＇s good performance with all these strategies on classic vehicle routing problem with time windows（VRPTW） benchmark instances and the TDVRPTW instances, and some better results especially for the number of vehicles and travel times of the best solutions are obtained in comparison with the previous research.展开更多
Unmanned combat air vehicles(UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCA...Unmanned combat air vehicles(UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCAV can carry different weapons to accomplish different combat missions. Choice of different weapons will have different effects on the final combat effectiveness. This work presents a mixed integer programming model for simultaneous weapon configuration and route planning of UCAVs, which solves the problem optimally using the IBM ILOG CPLEX optimizer for simple missions. This paper develops a heuristic algorithm to handle the medium-scale and large-scale problems. The experiments demonstrate the performance of the heuristic algorithm in solving the medium scale and large scale problems. Moreover, we give suggestions on how to select the most appropriate algorithm to solve different scale problems.展开更多
The multi-compartment electric vehicle routing problem(EVRP)with soft time window and multiple charging types(MCEVRP-STW&MCT)is studied,in which electric multi-compartment vehicles that are environmentally friendl...The multi-compartment electric vehicle routing problem(EVRP)with soft time window and multiple charging types(MCEVRP-STW&MCT)is studied,in which electric multi-compartment vehicles that are environmentally friendly but need to be recharged in course of transport process,are employed.A mathematical model for this optimization problem is established with the objective of minimizing the function composed of vehicle cost,distribution cost,time window penalty cost and charging service cost.To solve the problem,an estimation of the distribution algorithm based on Lévy flight(EDA-LF)is proposed to perform a local search at each iteration to prevent the algorithm from falling into local optimum.Experimental results demonstrate that the EDA-LF algorithm can find better solutions and has stronger robustness than the basic EDA algorithm.In addition,when comparing with existing algorithms,the result shows that the EDA-LF can often get better solutions in a relatively short time when solving medium and large-scale instances.Further experiments show that using electric multi-compartment vehicles to deliver incompatible products can produce better results than using traditional fuel vehicles.展开更多
This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the ...This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.展开更多
在经典车辆路径问题(vehicle routing problem,VRP)的基础上增加了客户要求访问的时间窗约束,以车辆行驶路径最短和使用车辆数最小为目标,建立了不确定车辆数的多约束车辆路径问题(multi-constraint vehicle routing problem with varia...在经典车辆路径问题(vehicle routing problem,VRP)的基础上增加了客户要求访问的时间窗约束,以车辆行驶路径最短和使用车辆数最小为目标,建立了不确定车辆数的多约束车辆路径问题(multi-constraint vehicle routing problem with variable fleets,MVRP-VF)的数学模型。引入遗传算法的交叉操作以及大规模邻域搜索算法中的破坏算子和修复算子,重新定义了基本灰狼优化算法(grey wolf optimizer,GWO)的操作算子,优化了GWO的寻优机制,从而设计出用于求解MVRP-VF问题的混合灰狼优化算法(hybrid grey wolf optimizer,HGWO)。通过仿真实验与其他参考文献中的算法求解结果进行比较,验证了HGWO求解该类问题的有效性与可行性。展开更多
在经典的车辆路径优化问题的基础上,考虑顾客有同时取货和送货的需求,且每个顾客都有独立的时间窗,研究带时间窗和同时取送货的车辆路径问题(VRPSPDTW)。提出模拟退火算法求解该问题,算法使用Residual capacity and radial surcharge(RC...在经典的车辆路径优化问题的基础上,考虑顾客有同时取货和送货的需求,且每个顾客都有独立的时间窗,研究带时间窗和同时取送货的车辆路径问题(VRPSPDTW)。提出模拟退火算法求解该问题,算法使用Residual capacity and radial surcharge(RCRS)算法求得初始解,通过模拟退火过程和4种局部搜索方法(路径内搜索:2-opt法和or-opt法;路径间搜索:swap/shift法和2-opt*法)进行优化,并选取Wang和Chen测试数据集中的15个算例对算法性能进行测试。测试结果表明,提出的模拟退火算法优于Wang和Chen的遗传算法,能有效地求解VRPSPDTW问题,并且可以被灵活的扩展解决其他车辆路径问题和组合优化问题。展开更多
文摘The time dependent vehicle routing problem with time windows（TDVRPTW） is considered. A multi-type ant system（MTAS） algorithm hybridized with the ant colony system（ACS）and the max-min ant system（MMAS） algorithms is proposed. This combination absorbs the merits of the two algorithms in solutions construction and optimization separately. In order to improve the efficiency of the insertion procedure, a nearest neighbor selection（NNS） mechanism, an insertion local search procedure and a local optimization procedure are specified in detail. And in order to find a balance between good scouting performance and fast convergence rate, an adaptive pheromone updating strategy is proposed in the MTAS. Computational results confirm the MTAS algorithm＇s good performance with all these strategies on classic vehicle routing problem with time windows（VRPTW） benchmark instances and the TDVRPTW instances, and some better results especially for the number of vehicles and travel times of the best solutions are obtained in comparison with the previous research.
基金supported by the National Natural Science Foundation of China(7147117571471174)
文摘Unmanned combat air vehicles(UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCAV can carry different weapons to accomplish different combat missions. Choice of different weapons will have different effects on the final combat effectiveness. This work presents a mixed integer programming model for simultaneous weapon configuration and route planning of UCAVs, which solves the problem optimally using the IBM ILOG CPLEX optimizer for simple missions. This paper develops a heuristic algorithm to handle the medium-scale and large-scale problems. The experiments demonstrate the performance of the heuristic algorithm in solving the medium scale and large scale problems. Moreover, we give suggestions on how to select the most appropriate algorithm to solve different scale problems.
基金supported by the National Natural Science Foundation of China(71571076)the National Key R&D Program for the 13th-Five-Year-Plan of China(2018YFF0300301).
文摘The multi-compartment electric vehicle routing problem(EVRP)with soft time window and multiple charging types(MCEVRP-STW&MCT)is studied,in which electric multi-compartment vehicles that are environmentally friendly but need to be recharged in course of transport process,are employed.A mathematical model for this optimization problem is established with the objective of minimizing the function composed of vehicle cost,distribution cost,time window penalty cost and charging service cost.To solve the problem,an estimation of the distribution algorithm based on Lévy flight(EDA-LF)is proposed to perform a local search at each iteration to prevent the algorithm from falling into local optimum.Experimental results demonstrate that the EDA-LF algorithm can find better solutions and has stronger robustness than the basic EDA algorithm.In addition,when comparing with existing algorithms,the result shows that the EDA-LF can often get better solutions in a relatively short time when solving medium and large-scale instances.Further experiments show that using electric multi-compartment vehicles to deliver incompatible products can produce better results than using traditional fuel vehicles.
基金supported by the National Natural Science Foundation of China (61963022,51665025,61873328)。
文摘This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.
文摘在经典车辆路径问题(vehicle routing problem,VRP)的基础上增加了客户要求访问的时间窗约束,以车辆行驶路径最短和使用车辆数最小为目标,建立了不确定车辆数的多约束车辆路径问题(multi-constraint vehicle routing problem with variable fleets,MVRP-VF)的数学模型。引入遗传算法的交叉操作以及大规模邻域搜索算法中的破坏算子和修复算子,重新定义了基本灰狼优化算法(grey wolf optimizer,GWO)的操作算子,优化了GWO的寻优机制,从而设计出用于求解MVRP-VF问题的混合灰狼优化算法(hybrid grey wolf optimizer,HGWO)。通过仿真实验与其他参考文献中的算法求解结果进行比较,验证了HGWO求解该类问题的有效性与可行性。
文摘在经典的车辆路径优化问题的基础上,考虑顾客有同时取货和送货的需求,且每个顾客都有独立的时间窗,研究带时间窗和同时取送货的车辆路径问题(VRPSPDTW)。提出模拟退火算法求解该问题,算法使用Residual capacity and radial surcharge(RCRS)算法求得初始解,通过模拟退火过程和4种局部搜索方法(路径内搜索:2-opt法和or-opt法;路径间搜索:swap/shift法和2-opt*法)进行优化,并选取Wang和Chen测试数据集中的15个算例对算法性能进行测试。测试结果表明,提出的模拟退火算法优于Wang和Chen的遗传算法,能有效地求解VRPSPDTW问题,并且可以被灵活的扩展解决其他车辆路径问题和组合优化问题。
