Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of t...Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.展开更多
As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of c...As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.展开更多
Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the s...Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge.In this paper,we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics,integrating conceptual analysis,conceptual modeling,quantitative modeling and simulation implementation.We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition,thus classifying the related battle damage knowledge logically.Then,we construct the conceptual model of influencing factors of battle damage by using Entity-Relations hip approach,thus describing their interactions reasonably.Subsequently,we extract the important influencing factors by using social network analysis,thus evaluating their importance quantitatively and further clarifying the elements of simulation.Finally,we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input,and obtain simulation model output,i.e.,new battle damage laws knowledge,thus verifying feasibility and effectiveness of the proposed method.The results show that this method can be used to support human decision-making and action.展开更多
随着经济的发展,城市交通路网拓扑的日益复杂且交通状况突发多变,传统的设定客户间道路唯一且通行状态不变的动态车辆路径规划模型很难有效指导物流企业进行物流配送作业.本文利用智慧交通系统,结合物流配送作业需求,构建了分时段的动...随着经济的发展,城市交通路网拓扑的日益复杂且交通状况突发多变,传统的设定客户间道路唯一且通行状态不变的动态车辆路径规划模型很难有效指导物流企业进行物流配送作业.本文利用智慧交通系统,结合物流配送作业需求,构建了分时段的动态交通路网模型,量化了不同类型的城市道路对物流车辆调度与路径规划的影响,以燃油、时间窗、司机等综合成本最低为目标,建立了考虑城市道路分级与动态交通路网的动态车辆路径问题(DVRP-RD,Dynamic Vehicle Route Problem with Road Condition)的两阶段混合整数模型,改进了遗传算法对其进行求解.最后,以深圳市的南山区与宝安区的真实路网为例,模拟了不同规模的客户需求与3种不同的动态更新机制,实验结果表明该方案与模型可以有效的为物流企业降低城市物流配送成本、提高调度效率与改善服务质量.展开更多
基金Project(51178061)supported by the National Natural Science Foundation of ChinaProject(2010FJ6016)supported by Hunan Provincial Science and Technology,China+1 种基金Project(12C0015)supported by Scientific Research Fund of Hunan Provincial Education Department,ChinaProject(13JJ3072)supported by Hunan Provincial Natural Science Foundation of China
文摘Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.
基金Project(2011ZK2030)supported by the Soft Science Research Plan of Hunan Province,ChinaProject(2010ZDB42)supported by the Social Science Foundation of Hunan Province,China+1 种基金Projects(09A048,11B070)supported by the Science Research Foundation of Education Bureau of Hunan Province,ChinaProjects(2010GK3036,2011FJ6049)supported by the Science and Technology Plan of Hunan Province,China
文摘As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.
基金This research was funded by National Natural Science Foundation of China(grant number 61473311,70901075)Natural Science Foundation of Beijing Municipality(grant number 9142017)military projects funded by the Chinese Army.
文摘Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge.In this paper,we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics,integrating conceptual analysis,conceptual modeling,quantitative modeling and simulation implementation.We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition,thus classifying the related battle damage knowledge logically.Then,we construct the conceptual model of influencing factors of battle damage by using Entity-Relations hip approach,thus describing their interactions reasonably.Subsequently,we extract the important influencing factors by using social network analysis,thus evaluating their importance quantitatively and further clarifying the elements of simulation.Finally,we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input,and obtain simulation model output,i.e.,new battle damage laws knowledge,thus verifying feasibility and effectiveness of the proposed method.The results show that this method can be used to support human decision-making and action.
文摘随着经济的发展,城市交通路网拓扑的日益复杂且交通状况突发多变,传统的设定客户间道路唯一且通行状态不变的动态车辆路径规划模型很难有效指导物流企业进行物流配送作业.本文利用智慧交通系统,结合物流配送作业需求,构建了分时段的动态交通路网模型,量化了不同类型的城市道路对物流车辆调度与路径规划的影响,以燃油、时间窗、司机等综合成本最低为目标,建立了考虑城市道路分级与动态交通路网的动态车辆路径问题(DVRP-RD,Dynamic Vehicle Route Problem with Road Condition)的两阶段混合整数模型,改进了遗传算法对其进行求解.最后,以深圳市的南山区与宝安区的真实路网为例,模拟了不同规模的客户需求与3种不同的动态更新机制,实验结果表明该方案与模型可以有效的为物流企业降低城市物流配送成本、提高调度效率与改善服务质量.
