摘要
针对产出单一产品的多级农产品供应链网络优化设计问题,同时考虑最小化总成本和最大化客户需求满足率两个目标,建立了集成生产设施选址、产能决策和物流网络运输模式选择的农产品供应链网络优化设计的多目标混合整数规划数学模型。基于一种新型的改进二元粒子群算法并融合拥挤距离计算和外部Pareto档案构建等技术,提出一种Pareto多目标粒子群优化算法求解农产品供应链网络设计问题。通过将该算法与基础二元粒子群优化扩展而来的多目标粒子群优化,以及非支配排序遗传算法应用于三个案例的计算对比,验证了算法的有效性和优越性。
Aiming at the optimization design problem of Agri-food Supply Chain Network （ASCN）, by considering minimum total cost and maximum demand fill rate, a multi-objective mixed integer linear programming model was presented which integrated the decisions on facility location, capacity selection and transportation mode selection for logistics network. A Multi-objective Modified Particle Swarm Optimization （MoMPSO） algorithm based on new im- proved binary PSO with techniques of computing crowding distance calculation and external Pareto archive construc- tion was developed. Through comparing MoMPSO with existing Multi-objective Basic binary PSO （MoBPSO） and the famous NSGA-II against three cases, the effectiveness and superiority of proposed algorithm was verified.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2015年第9期2515-2527,共13页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(71403114
71373116)
江苏省高校哲学社会科学研究基金资助项目(2014SJB135)
粮食公益性行业科研专项资助项目(201513004)
江苏高校优势学科建设工程资助项目~~
关键词
农产品供应链网络
多目标优化
混合整数规划
粒子群优化算法
agri-food supply chain network
multi-objective optimization mixed integer linear programming
particleswarm optimization
