Energy-Efficient Hybrid Flowshop Scheduling with Consistent Sublots Using an Improved Cooperative Coevolutionary Algorithm

Chengshuai Li, Biao Zhang (), Yuyan Han (), Yuting Wang, Junqing Li and Kaizhou Gao
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Chengshuai Li: School of Computer Science, Liaocheng University, Liaocheng 252059, China
Biao 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, Taipa, Macau 999078, China

Mathematics, 2022, vol. 11, issue 1, 1-27

Abstract: Energy conservation, emission reduction, and green and low carbon are of great significance to sustainable development, and are also the theme of the transformation and upgrading of the manufacturing industry. This paper concentrates on studying the energy-efficient hybrid flowshop scheduling problem with consistent sublots (HFSP_ECS) with the objective of minimizing the energy consumption. To solve the problem, the HFSP_ECS is decomposed by the idea of “divide-and-conquer”, resulting in three coupled subproblems, i.e., lot sequence, machine assignment, and lot split, which can be solved by using a cooperative methodology. Thus, an improved cooperative coevolutionary algorithm (vCCEA) is proposed by integrating the variable neighborhood descent (VND) strategy. In the vCCEA, considering the problem-specific characteristics, a two-layer encoding strategy is designed to represent the essential information, and a novel collaborative model is proposed to realize the interaction between subproblems. In addition, special neighborhood structures are designed for different subproblems, and two kinds of enhanced neighborhood structures are proposed to search for potential promising solutions. A collaborative population restart mechanism is established to ensure the population diversity. The computational results show that vCCEA can coordinate and solve each subproblem of HFSP_ECS effectively, and outperform the mathematical programming and the other state-of-the-art algorithms.

Keywords: hybrid flowshop scheduling; energy efficiency; consistent sublots; collaborative coevolutionary algorithm; variable neighborhood descent (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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