基于进化算法的多目标闭环物流网络设计  

Evolutionary Algorithm for Multi-Objective Closed-Loop Logistics Network Design

作　　者：涂南[1] 戴雯婧[1] 麦合迪[1] 

机构地区：[1]清华大学深圳研究生院,广东深圳518055

出　　处：《工业工程》2013年第2期59-66,共8页Industrial Engineering Journal

摘　　要：为了帮助生产企业建立科学合理的闭环物流网络系统,提高废旧产品材料的再循环利用率,提出了一个多周期、多产品、多阶段的闭环物流网络选址与运输模型。该模型中,不仅考虑建造混合分销回收中心,还提出了2个优化目标:经济成本最小和时间成本最小。针对该多目标优化问题,本文采用了一种基于优先值编码方法的进化算法对模型求解,最终得到该问题的帕累托(Pareto)前沿。通过与约束法的计算结果相比较,求得误差均值小于5%,说明该进化算法对Pareto前沿的拟合程度较好,计算结果是正确有效的。For a closed-loop logistics, it is important to design a network such that it can operate effective- ly and at the same time recycling rate of waste materials can be increased. It is assumed that hybrid distri- bution and collection center is adopted for the system. A muhi-product, multi-period, and multi-stage closed-loop logistics network location and transportation model is presented for this purpose. It is a multi- objective optimization model for minimizing both economic cost and time. In order to solve this problem, an evolutionary algorithm with a priority-based encoding method is proposed, leading to the Pareto front. The proposed method is compared with the constraint method. Results show that, by the proposed method, the average error is less than 5%. In other words, the proposed evolutionary algorithm describes Pareto front well, and its results are correct and reasonable.

关 键 词：闭环物流 多目标优化 进化算法 

分 类 号：F403.3[经济管理—产业经济]