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基于提前期的码头与供应链多Agent策略协同及优化
引用本文:周建频.基于提前期的码头与供应链多Agent策略协同及优化[J].西南交通大学学报,2013,26(6):1129-1135.
作者姓名:周建频
基金项目:福建省自然科学基金资助项目(2013J01264)
摘    要:针对国际供应与分销网络中流程提前期的较大不确定性,提出了码头系统与供应链相结合的多Agent策略协调框架,建立了基于策略提前期的循环优化决策模型.在对供应链响应性有不同要求的情况下,对国际供应链节点码头前方作业系统平均流程时间选择合适的控制策略,调节国际供应链补货提前期的波动范围,以驱动供应链时间和成本两方面绩效目标的权衡优化.采用多目标优化遗传算法与神经网络相结合,以一个集装箱码头采取面向供应链策略的计划决策过程为例进行仿真,结果表明:提出的决策模式可增强码头策略计划与时间敏感型供应链整体目标的协同效应;虽然调节提前期波动区间码头需要付出较大的作业均衡成本,但获得的时间目标确定性会明显改善供应网络总体的绩效水平. 

关 键 词:供应链    码头策略计划    提前期    Agents    多目标优化    遗传算法
收稿时间:2013-05-15

Lead-Time Based Multi-agent Policies Synergy and Optimization between Quay and Supply Chains
ZHOU Jianpin.Lead-Time Based Multi-agent Policies Synergy and Optimization between Quay and Supply Chains[J].Journal of Southwest Jiaotong University,2013,26(6):1129-1135.
Authors:ZHOU Jianpin
Abstract:Targeting the great uncertainty of the process lead time in the international supply and distribution networks, the paper proposed a coordination framework of mixed multi-agent policies between the quay system and supply chains, and built a loop optimization decision-making model based on the tactical lead time. According to the different requirements for the supply chain responsiveness, suitable policies were chosen to control the mean flow time of the quay front operating system in an international supply chain node, to regulate the lead time fluctuation of the international supply chains, and to drive the goal optimization of the supply chain performance between time and cost. The research adopted a combination of multi-objective optimization genetic algorithm and neural network and used an example of simulating the planning decision process of supply chain oriented policies adopted by a container quay. The results demonstrated that the proposed policies could enhance the synergy effects between the quay tactical planning and the goals of time-sensitive supply chains. Although more operational equilibrium cost was needed to regulate the lead time fluctuation, the obtained certainties of the time goal can evidently improve the overall performance of the supply chain network. 
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