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Article type: Research Article
Authors: Luan, Feia; b; * | Tang, Biaoa | Li, Yec | Liu, Shi Qiangd | Yang, Xueqina | Masoud, Mahmoude; f | Feng, Baoyug
Affiliations: [a] College of Mechanical and Electrical Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China | [b] Shaanxi Research Institute of Agricultural Products Processing Technology, Xi’an, Shaanxi, China | [c] Ulster College, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China | [d] School of Economics and Management, Fuzhou University, Fuzhou, Fujian, China | [e] Department of Information Systems and Operations Management, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia | [f] Center for Smart Mobility and Logistics, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia | [g] Xi’an Natural Gas Engineering Co., Ltd, Xi’an, Shaanxi, China
Correspondence: [*] Corresponding author. Fei Luan, E-mail: luanfei@sust.edu.cn; ORCID: 0000-0002-9398-2343.
Abstract: As environmental contamination becomes more and more severe, enterprises need to consider optimizing environmental criteria while optimizing production criteria. In this study, a multi-objective green flexible job shop scheduling problem (MO_GFJSP) is established with two objective functions: the makespan and the carbon emission. To effectively solve the MO_GFJSP, an improved chimp optimization algorithm (IChOA) is designed. The proposed IChOA has four main innovative aspects: 1) the fast non-dominated sorting (FDS) method is introduced to compare the individuals with multiple objectives and strengthen the solution accuracy. 2) a dynamic convergence factor (DCF) is introduced to strengthen the capabilities of exploration and exploitation. 3) the position weight (PW) is used in the individual position updating to enhance the search efficiency. 4) the variable neighborhood search (VNS) is developed to strengthen the capacity to escape the local optimum. By executing abundant experiments using 20 benchmark instances, it was demonstrated that the developed IChOA is efficient to solve the MO_GFJSP and effective for reducing carbon emission in the flexible job shop.
Keywords: Multi-objective green flexible job shop scheduling, meta-heuristics, improved chimp optimization algorithm, variable neighborhood search
DOI: 10.3233/JIFS-236157
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 4, pp. 7697-7710, 2024
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