A novel heuristic method for the energy-efficient flexible job-shop scheduling problem with sequence-dependent set-up and transportation time - Zhang, Hongliang; Xu, Gongjie; Pan, Ruilin; Ge, Haijiang (Engineering optimization, 2022)
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.