文献类型：期刊文献

英文题名：Production planning for stochastic manufacturing/remanufacturing system with demand substitution using a hybrid ant colony system algorithm

作者：Liu, Wenjie[1];Ma, Wenyan[1];Hu, Yi[2];Jin, Mingzhou[3,4];Li, Kai[5];Chang, Xiangyun[6];Yu, Xianyu[1]

机构：[1]Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, Nanjing 211106, Jiangsu, Peoples R China;[2]Yangtze Memory Technol Co Ltd, Wuhan 430000, Hubei, Peoples R China;[3]Cent South Univ Forestry & Technol, Coll Logist & Transportat Engn, Changsha 410004, Hunan, Peoples R China;[4]Univ Tennessee, Dept Ind & Syst Engn, Knoxville, TN 37996 USA;[5]Hefei Univ Technol, Dept Business Adm, Hefei 230009, Anhui, Peoples R China;[6]East China Univ Sci & Technol, Dept Management Sci & Engn, Shanghai 200237, Peoples R China

年份：2019

卷号：213

起止页码：999

外文期刊名：JOURNAL OF CLEANER PRODUCTION

收录：;EI(收录号：20190206361031);WOS:【SCI-EXPANDED(收录号:WOS:000461132600089)】；

基金：This work is supported by grants from the National Natural Science Foundation of China (71871117, 71273131, 71473085, 7167 1090), Humanities and Social Science Foundation of Ministry of Education of China (18YJA630066), Key Project of University Social Sciences Foundation of Jiangsu Province of China (2017ZDIXM083), Aeronautical Science Fund of China (2017ZG52080).

语种：英文

外文关键词：Production planning; Hybrid manufacturing/remanufacturing system; Demand substitution; Ant colony system algorithm with random sampling method

摘要：A hybrid manufacturing/remanufacturing system (HMRS) is an effective tool to address the global challenge of resource depletion and environmental deterioration. This paper aims to make an optimal production plan for a stochastic HMRS with demand substitution. To achieve the above objective, a multi-period mixed integer programming model was first constructed. An ant colony system algorithm with random sampling method (ACS-RSM) was proposed to minimize the total expected cost of the stochastic HMRS. Finally, the proposed model and ACS-RSM algorithm were applied to an auto alternator case. The effects of the used product recovery rate and batch sizes of new and remanufactured products on the total expected cost were analyzed. The research results showed that the ACS-RSM algorithm performed well regarding computational efficiency and solution quality. There were two major findings through the practical case study. The first finding was that with increase of recovery rate of used product, total expected cost of the HMRS declined dramatically until a certain point. When the recovery rate was greater than 91%, the total expected cost kept almost constant. The second finding was that when the batch sizes of the new product and remanufactured product rose, the total expected cost had an obvious increase and the running time of the ACS-RSM algorithm decreased monotonically. The study yields an effective decision-making tool for optimizing the production plan of the stochastic HMRS with demand substitution. (C) 2018 Elsevier Ltd. All rights reserved.