Linear Disassembly Line Balancing Problem with Tool Deterioration and Solution by Discrete Migratory Bird Optimizer

Author:

Qin Shujin12ORCID,Wang Jiaxin3,Wang Jiacun4ORCID,Guo Xiwang2ORCID,Qi Liang5ORCID,Fu Yaping6

Affiliation:

1. Research Center of the Economic and Social Development of Henan East Provincial Joint, Shangqiu Normal University, Shangqiu 476000, China

2. College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China

3. Artificial Intelligence and Software College, Liaoning Petrochemical University, Fushun 113001, China

4. Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ 07764, USA

5. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China

6. School of Business, Qingdao University, Qingdao 266071, China

Abstract

In recent years, the global resource shortage has become a serious issue. Recycling end-of-life (EOL) products is conducive to resource reuse and circular economy and can mitigate the resource shortage issue. The disassembly of EOL products is the first step for resource reuse. Disassembly activities need tools, and tool deterioration occurs inevitably during the disassembly process. This work studies the influence of tool deterioration on disassembly efficiency. A disassembly line balancing model with the goal of maximizing disassembly profits is established, in which tool selection and assignment is a critical part. A modified discrete migratory bird optimizer is proposed to solve optimization problems. The well-known IBM CPLEX optimizer is used to verify the correctness of the model. Six real-world products are used for disassembly experiments. The popular fruit fly optimization algorithm, whale optimization algorithm and salp swarm algorithm are used for search performance comparison. The results show that the discrete migratory bird optimizer outperforms all three other algorithms in all disassembly instances.

Funder

National Natural Science Foundation of China

Liaoning 428 Revitalization Talents Program

Publisher

MDPI AG

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