Multi-objective optimization for a closed-loop network design problem using an improved genetic algorithm

作     者：Shi, Jianmai Liu, Zhong Tang, Luohao Xiong, Jian 

作者机构：Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China 

出 版 物：《APPLIED MATHEMATICAL MODELLING》 (应用数学模型)

年 卷 期：2017年第45卷

页      面：14-30页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 0801[工学-力学（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China department of education of Hunan province [YB2013B011] 

主　　题：Closed loop supply chain Carbon emission Multi-objective programming Facility location Evaluation algorithm 

摘      要：This paper develops a multi-objective Mixed Integer Programming model for a closed-loop network design problem. In addition to the overall costs, the model optimizes overall carbon emissions and the responsiveness of the network. An improved genetic algorithm based on the framework of NSGA II is developed to solve the problem and obtain Pareto-optimal solutions. An example with 95 cities in China is presented to illustrate the approach. Through randomly generated examples with different sizes;the computational performance of the proposed algorithm is also compared with former genetic algorithms in the literature employing the weight-sum technique as a fitness evaluation strategy. Computational results indicate that the proposed algorithm can obtain superior Pareto-optimal solutions. (C) 2016 Elsevier Inc. All rights reserved.