摘要
为了提高后端集中冗余供应链的决策规划能力,提出基于智能粒子群规划的后端集中冗余供应链决策模型。构建后端集中冗余供应链的分布式节点部署模型及供应链网络的最优规划路径,采用线性规划方法提取后端集中冗余供应链路径输出的高阶统计特征量,结合模糊关联规则调度方法进行后端集中冗余供应链的决策模型优化构造;采用智能粒子群寻优算法对决策模型进行求解,选出最优决策方案,实现后端集中冗余供应链的优化决策和控制。仿真结果表明,采用上述模型进行后端集中冗余供应链规划的资源消耗较小,空间规划能力较强,提高了供应链配送路径寻优和智能控制能力。
In order to improve the decision planning ability,a decision-making model of back-end centralized redundancy supply chain based on intelligent particle swarm planning was presented.At first,the distributed node deployment model of back-end centralized redundant supply chain and the optimal planning path of supply chain network were constructed.Then,the linear programming method was used to extract the high-order statistical char-acteristics of path output of back-end centralized redundant supply chain.Moreover,the fuzzy association rule scheduling method was used to optimize the decision model of back-end centralized redundant supply chain.Final-ly,the intelligent particle swarm optimization algorithm was used to solve the decision-making model select and the optimal decision-making scheme.Thus,the optimal decision-making and control for the back-end centralized re-dundant supply chain was achieved.Simulation results show that the proposed model has less resource consumption and stronger spatial planning ability,so that the supply chain distribution path optimization and intelligent control a-bility can be improved.
作者
贾强法
JIA Qiang-fa(Sias International University,Zhengzhou University,Zhengzhou Henan 451150,China)
出处
《计算机仿真》
北大核心
2020年第12期345-348,444,共5页
Computer Simulation
关键词
后端集中冗余供应链
决策模型
规划
寻优
粒子群
Back-end centralized redundant supply chain
Decision-making model
Planning
Optimization
Particle swarm
