An MILP Model for Energy-Conscious Flexible Job Shop Problem with Transportation and Sequence-Dependent Setup Times

Leilei Meng (), Biao Zhang, Kaizhou Gao and Peng Duan
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Leilei Meng: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Biao Zhang: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Kaizhou Gao: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Peng Duan: School of Computer Science, Liaocheng University, Liaocheng 252059, China

Sustainability, 2022, vol. 15, issue 1, 1-14

Abstract: As environmental awareness grows, energy-aware scheduling is attracting increasing attention. Compared with traditional flexible job shop scheduling problem (FJSP), FJSP, with considering sequence-dependent setup times and transportation times (FJSP-SDST-T), is closer to real production. In existing research, little research has focused on FJSP-SDST-T with the minimization energy consumption. In order to make up the gap, a mixed integer linear programming (MILP) model has been formulated to solve FJSP-SDST-T with minimizing energy. Firstly, the total energy consumption of the workshop included the processing energy consumption, setup energy consumption, idle energy consumption, transportation energy consumption and common energy consumption, which were analyzed and formulated by introducing related decision variables. Then, the MILP model was detailedly formulated from the formulation of the energy consumption composition, the objective function, the decision variables and the constraint sets and the linearization. Finally, experiments were carried out on extended benchmark cases and the results showed the effectiveness of the MILP model.

Keywords: energy consumption; flexible job shop scheduling; sequence-dependent setup times; transportation times; mixed integer linear programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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