Multi-objective optimization of energy-efficient remanufacturing system scheduling problem with lot-streaming production mode

被引:19
作者
Tian, Guangdong [1 ,3 ]
Wang, Wenjie [2 ,3 ]
Zhang, Honghao [3 ]
Zhou, Xiaowan [4 ]
Zhang, Cheng [5 ]
Li, Zhiwu [6 ]
机构
[1] Beijing Univ Civil Engn & Architecture, Sch Mech Elect & Vehicle Engn, Beijing 100044, Peoples R China
[2] Zhengzhou Univ, Sch Mech & Power Engn, Zhengzhou 450001, Peoples R China
[3] Shandong Univ, Sch Mech Engn, Jinan 250061, Peoples R China
[4] Zhengzhou Univ, Sch Comp & Artificial Intelligence, Zhengzhou 450001, Peoples R China
[5] China Acad Machinery Sci & Technol Grp Co Ltd, Qingdao 266300, Peoples R China
[6] Macau Univ Sci & Technol, Inst Syst Engn, Taipa 999078, Macau, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Green manufacturing; Remanufacturing system scheduling; Energy -efficient scheduling; Lot; -streaming; Multi -objective optimization; FLOW-SHOP; EVOLUTIONARY ALGORITHM; GENETIC ALGORITHM; SEARCH; PERFORMANCE;
D O I
10.1016/j.eswa.2023.121309
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Most previous studies on the scheduling problem in remanufacturing systems have focused on single or two production stages and economic criteria such as makespan or tardiness. However, environmental criteria like energy consumption or carbon emissions, as well as the lot-streaming production mode, have not been adequately addressed. This paper presents a novel approach to the energy-efficient remanufacturing system scheduling problem with lot-streaming production mode (ERSSP-LS) for the first time, which integrates disassembly, reprocessing, and reassembly three pivotal production stages. Firstly, a multi-objective mathematical model aimed at simultaneously minimizing the total energy consumption (TEC) and makespan (Cmax) is established and presented. To further reduce the TEC, the well-accepted energy-saving measure, known as the turn off and on strategy, is also integrated. Subsequently, a hybrid multi-objective optimization algorithm called HMOFFO, which combines the fruit fly optimization algorithm and simulated annealing mechanism is developed to seek the promising Pareto solution set. Finally, several experiments on a real-life case and a group of ten random test instances are carried out and the computational results affirm the feasibility and effectiveness of the proposed HMOFFO in solving the ERSSP-LS.
引用
收藏
页数:20
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