A Distributed Blocking Flowshop Scheduling with Setup Times Using Multi-Factory Collaboration Iterated Greedy Algorithm

Chenyao Zhang, Yuyan Han (), Yuting Wang (), Junqing Li and Kaizhou Gao
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Chenyao Zhang: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Yuyan Han: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Yuting Wang: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Junqing Li: School of Computer Science, Shandong Normal University, Jinan 252000, China
Kaizhou Gao: Macau Institute of Systems Engineering, Macau University of Science and Technology, Macau 999078, China

Mathematics, 2023, vol. 11, issue 3, 1-25

Abstract: As multi-factory production models are more widespread in modern manufacturing systems, a distributed blocking flowshop scheduling problem (DBFSP) is studied in which no buffer between adjacent machines and setup time constraints are considered. To address the above problem, a mixed integer linear programming (MILP) model is first constructed, and its correctness is verified. Then, an iterated greedy-algorithm-blending multi-factory collaboration mechanism (mIG) is presented to optimize the makespan criterion. In the mIG algorithm, a rapid evaluation method is designed to reduce the time complexity, and two different iterative processes are selected by a certain probability. In addition, collaborative interactions between cross-factory and inner-factory are considered to further improve the exploitation and exploration of mIG. Finally, the 270 tests showed that the average makespan and RPI values of mIG are 1.93% and 78.35% better than the five comparison algorithms on average, respectively. Therefore, mIG is more suitable to solve the studied DBFSP_SDST.

Keywords: blocking; iterated greedy algorithm; distributed flowshop scheduling; multi-factory collaborative strategy; makespan (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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