A novel heuristic method for the energy-efficient flexible job-shop scheduling problem with sequence-dependent set-up and transportation time

• Published in: Engineering optimization Vol. 54; no. 10; pp. 1646 - 1667
• Main Authors: Zhang, Hongliang, Xu, Gongjie, Pan, Ruilin, Ge, Haijiang
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 03.10.2022; Taylor & Francis Ltd
• Subjects: Algorithms; Energy consumption; FJSP; Heuristic job shop scheduling; Heuristic methods; Integer programming; Iterative methods; Job shop scheduling; Linear programming; Mixed integer; NHM; sequence-dependent set-up time; Transportation; transportation time
• ISSN: 0305-215X; 1029-0273
• DOI: 10.1080/0305215X.2021.1949007

With the increasing attention on environmental issues, green scheduling in manufacturing industries has become a hot research topic. As a typical scheduling problem, the flexible job-shop scheduling problem (FJSP) has received increasing attention, but research on the FJSP considering set-up and transportation times simultaneously is still rare. To address the energy-efficient FJSP with sequence-dependent set-up and transportation times to minimize makespan and total energy consumption, a multi-objective mixed-integer linear programming model of the problem is formulated and an effective novel heuristic method (NHM) is proposed. To enhance the convergence and distribution of the NHM, three strategies-population initialization, greedy iterative decoding and local intensification-are designed. The performance of the NHM is demonstrated by comparison with three algorithms through 48 instances. The results show that the NHM can obtain a scheduling scheme with lower makespan and total energy consumption than those of the comparison algorithms.