A Regular Production-Remanufacturing Inventory Model for a Two-Echelon System with Price-dependent Return Rate and Environmental Effects Investigation

International Conference on Mathematics: Education, Theory and Application

数学;教育

Dwicahyani, A.R.^1 ; Jauhari, W.A.^1 ; Jonrinaldi^2

Department of Industrial Engineering, Sebelas Maret University, Surakarta, Indonesia^1

Department of Industrial Engineering, Andalas University, Padang, Indonesia^2

关键词: Carbon emissions;    collector;    Inventory modeling;    refurbishing;    Reverse logistics;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/855/1/012013/pdf
DOI  :  10.1088/1742-6596/855/1/012013

学科分类：发展心理学和教育心理学

来源: IOP

【 摘 要 】

Product take-back recovery has currently became a promising effort for companies in order to create a sustainable supply chain. In addition, some restrictions including government regulations, social-ethical responsibilities, and up to economic factors have contributed to the reasons for the importance of product take-back recovery. This study aims to develop an inventory model in a system of reverse logistic management consisting of a manufacturer and a collector. Recycle dealer collects used products from the market and ships it to manufacturer. Manufacturer then recovers the used products and sell it eventually to the market. Some recovered products that can not be recovered as good as new one will be sold to the secondary market. In this study, we investigate the effects of environmental factors including GHG emissions and energy usage from transportation, regular production, and remanufacturing operations conducted by manufacturer and solve the model to get the maximum annual joint total profit for both parties. The model also considers price-dependent return rate and determine it as a decision variable as well as number of shipments from collector to manufacturer and optimal cycle period. An iterative procedure is proposed to determine the optimal solutions. We present a numerical example to illustrate the application of the model and perform a sensitivity analysis to study the effects of the changes in environmental related costs on the model's decision.