To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,...To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.展开更多
Stochastic vehicle routing problems ( VRPs) play important roles in logistics, though they have not been studied systematically yet. The paper summaries the definition, properties and classification of stochastic VRPs...Stochastic vehicle routing problems ( VRPs) play important roles in logistics, though they have not been studied systematically yet. The paper summaries the definition, properties and classification of stochastic VRPs, makes further discussion about two strategies in stochastic VRPs, and at last overviews dynamic and stochastic VRPs.展开更多
In response to the uncertainty of information of the injured in post disaster situations,considering constraints such as random chance and the quantity of rescue resource,the split deliv-ery vehicle routing problem wi...In response to the uncertainty of information of the injured in post disaster situations,considering constraints such as random chance and the quantity of rescue resource,the split deliv-ery vehicle routing problem with stochastic demands(SDVRPSD)model and the multi-depot split delivery heterogeneous vehicle routing problem with stochastic demands(MDSDHVRPSD)model are established.A two-stage hybrid variable neighborhood tabu search algorithm is designed for unmanned vehicle task planning to minimize the path cost of rescue plans.Simulation experiments show that the solution obtained by the algorithm can effectively reduce the rescue vehicle path cost and the rescue task completion time,with high optimization quality and certain portability.展开更多
Vehicle routing problem with time windows(VRPTW)is a core combinatorial optimization problem in distribution tasks.The electric vehicle routing problem with time windows under demand uncertainty and weight-related ene...Vehicle routing problem with time windows(VRPTW)is a core combinatorial optimization problem in distribution tasks.The electric vehicle routing problem with time windows under demand uncertainty and weight-related energy consumption is an extension of the VRPTW.Although some researchers have studied either the electric VRPTW with nonlinear energy consumption model or the impact of the uncertain customer demand on the conventional vehicles,the literature on the integration of uncertain demand and energy consumption of electric vehicles is still scarce.However,practically,it is usually not feasible to ignore the uncertainty of customer demand and the weight-related energy consumption of electronic vehicles(EVs)in actual operation.Hence,we propose the robust optimization model based on a route-related uncertain set to tackle this problem.Moreover,adaptive large neighbourhood search heuristic has been developed to solve the problem due to the NP-hard nature of the problem.The effectiveness of the method is verified by experiments,and the influence of uncertain demand and uncertain parameters on the solution is further explored.展开更多
针对有服务顺序限制的带时间窗的多需求多目标车辆路径问题(multi-demand and multi-objective vehicle routing problem with time window,MDMOVRPTW),在考虑多种需求由不同车辆按顺序服务等约束条件的同时,构建了最小化配送成本和最...针对有服务顺序限制的带时间窗的多需求多目标车辆路径问题(multi-demand and multi-objective vehicle routing problem with time window,MDMOVRPTW),在考虑多种需求由不同车辆按顺序服务等约束条件的同时,构建了最小化配送成本和最大化客户满意度的多目标模型。根据模型的特点设计了改进的哈里斯鹰优化(improved Harris hawks optimization,IHHO)算法,随机地将种群中部分支配解作为父代解,用临时组合算子和4种交叉算子搜索新解。最后,算例测试结果表明,相较于传统的哈里斯鹰优化算法,IHHO算法的求解性能得到了有效改善,各操作算子中交叉算子2的求解效果最好。将IHHO算法用于实例中,求解结果得到了改善,充分验证了IHHO算法的有效性。展开更多
针对模糊需求下的绿色两级车辆路径问题,以最小化车辆运营成本和油耗成本之和为优化目标,提出一种混合超启发式算法进行求解.首先,考虑两级问题解空间庞大且相互耦合,设计一种聚类分解策略将该问题分解为多个子问题,以合理缩小问题搜索...针对模糊需求下的绿色两级车辆路径问题,以最小化车辆运营成本和油耗成本之和为优化目标,提出一种混合超启发式算法进行求解.首先,考虑两级问题解空间庞大且相互耦合,设计一种聚类分解策略将该问题分解为多个子问题,以合理缩小问题搜索空间;然后,提出增强超启发式分布估计算法(enhanced hyperheuristic estimation of distribution algorithm,EHHEDA)对各个子问题进行求解,进而获得原问题的解.EHHEDA基于超启发式算法框架,在高层策略域设计一种基于三维概率模型的分布估计算法,动态确定由底层操作域中各搜索算子所组成的排列(即高层个体),可有效控制和引导整个算法的搜索行为;同时,在底层操作域设计10种有效邻域搜索算子,并加入重升温操作的模拟退火机制作为问题解(即底层个体)的接受准则,有利于在问题解空间中执行深入搜索.仿真实验结果表明,所提出的算法在大多数测试集上优于近年来用于求解类似问题的算法,验证了所提出算法的有效性.展开更多
基金supported by Natural Science Foundation Project of Gansu Provincial Science and Technology Department(No.1506RJZA084)Gansu Provincial Education Department Scientific Research Fund Grant Project(No.1204-13).
文摘To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.
基金Supported by the National Natural Science Fundation of China( No. 70071028 and 79700019).
文摘Stochastic vehicle routing problems ( VRPs) play important roles in logistics, though they have not been studied systematically yet. The paper summaries the definition, properties and classification of stochastic VRPs, makes further discussion about two strategies in stochastic VRPs, and at last overviews dynamic and stochastic VRPs.
基金supported by the National Natural Science Foundation of China(No.61903036)。
文摘In response to the uncertainty of information of the injured in post disaster situations,considering constraints such as random chance and the quantity of rescue resource,the split deliv-ery vehicle routing problem with stochastic demands(SDVRPSD)model and the multi-depot split delivery heterogeneous vehicle routing problem with stochastic demands(MDSDHVRPSD)model are established.A two-stage hybrid variable neighborhood tabu search algorithm is designed for unmanned vehicle task planning to minimize the path cost of rescue plans.Simulation experiments show that the solution obtained by the algorithm can effectively reduce the rescue vehicle path cost and the rescue task completion time,with high optimization quality and certain portability.
文摘Vehicle routing problem with time windows(VRPTW)is a core combinatorial optimization problem in distribution tasks.The electric vehicle routing problem with time windows under demand uncertainty and weight-related energy consumption is an extension of the VRPTW.Although some researchers have studied either the electric VRPTW with nonlinear energy consumption model or the impact of the uncertain customer demand on the conventional vehicles,the literature on the integration of uncertain demand and energy consumption of electric vehicles is still scarce.However,practically,it is usually not feasible to ignore the uncertainty of customer demand and the weight-related energy consumption of electronic vehicles(EVs)in actual operation.Hence,we propose the robust optimization model based on a route-related uncertain set to tackle this problem.Moreover,adaptive large neighbourhood search heuristic has been developed to solve the problem due to the NP-hard nature of the problem.The effectiveness of the method is verified by experiments,and the influence of uncertain demand and uncertain parameters on the solution is further explored.
文摘针对有服务顺序限制的带时间窗的多需求多目标车辆路径问题(multi-demand and multi-objective vehicle routing problem with time window,MDMOVRPTW),在考虑多种需求由不同车辆按顺序服务等约束条件的同时,构建了最小化配送成本和最大化客户满意度的多目标模型。根据模型的特点设计了改进的哈里斯鹰优化(improved Harris hawks optimization,IHHO)算法,随机地将种群中部分支配解作为父代解,用临时组合算子和4种交叉算子搜索新解。最后,算例测试结果表明,相较于传统的哈里斯鹰优化算法,IHHO算法的求解性能得到了有效改善,各操作算子中交叉算子2的求解效果最好。将IHHO算法用于实例中,求解结果得到了改善,充分验证了IHHO算法的有效性。
文摘针对模糊需求下的绿色两级车辆路径问题,以最小化车辆运营成本和油耗成本之和为优化目标,提出一种混合超启发式算法进行求解.首先,考虑两级问题解空间庞大且相互耦合,设计一种聚类分解策略将该问题分解为多个子问题,以合理缩小问题搜索空间;然后,提出增强超启发式分布估计算法(enhanced hyperheuristic estimation of distribution algorithm,EHHEDA)对各个子问题进行求解,进而获得原问题的解.EHHEDA基于超启发式算法框架,在高层策略域设计一种基于三维概率模型的分布估计算法,动态确定由底层操作域中各搜索算子所组成的排列(即高层个体),可有效控制和引导整个算法的搜索行为;同时,在底层操作域设计10种有效邻域搜索算子,并加入重升温操作的模拟退火机制作为问题解(即底层个体)的接受准则,有利于在问题解空间中执行深入搜索.仿真实验结果表明,所提出的算法在大多数测试集上优于近年来用于求解类似问题的算法,验证了所提出算法的有效性.
