Reverse supply chain optimisation with disassembly line balancing

作     者：Ozceylan, Eren Paksoy, Turan 

作者机构：Selcuk Univ Dept Ind Engn Konya Turkey 

出 版 物：《INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH》 (国际生产研究杂志)

年 卷 期：2013年第51卷第20期

页      面：5985-6001页

核心收录：

学科分类：12[管理学] 120202[管理学-企业管理（含：财务管理、市场营销、人力资源管理）] 0202[经济学-应用经济学] 02[经济学] 1202[管理学-工商管理] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0802[工学-机械工程] 

基　　金：Scientific and Technological Research Council of Turkey (TUBITAK) [111M040] Selcuk University Scientific Research Project Fund (BAP) 

主　　题：reverse supply chain optimisation disassembly line balancing non-linear mixed integer programming 

摘      要：Due to responding environmental issues, conforming governmental legislations and providing economic benefits, there has been a growing interest in recycling activities through the supply chains. Reverse supply chain (RSC) optimisation problem has a great potential as an efficient tactic to achieve this goal. While disassembly, one of the main activities in RSC, enables reuse and recycling of products and prevents the overuse, disassembly line balancing problem involves determination of a line design in which used products are partially/completely disassembled to obtain available components. The aim of this study is to optimise a RSC, involving customers, collection/disassembly centres and plants, that minimises the transportation costs while balancing the disassembly lines, which minimises the total fixed costs of opened workstations, simultaneously. A non-linear mixed-integer programming model, which simultaneously determines: (i) optimal distribution between the facilities with minimum cost, (ii) the number of disassembly workstations that will be opened with minimum cost, (iii) the cycle time in each disassembly centre and (iv) optimal assignment of tasks to workstations, is developed. A numerical example is given to illustrate the applicability of the proposed model. Different scenarios have been conducted to show the effects of sensitivity analyses on the performance measures of the problem.