Multi-objective Discrete Bat Optimizer for Partial U-shaped Disassembly Line Balancing Problem

Fuguang Huang, Laide Guo, Xiwang Guo, Shixin Liu, Liang Qi, Shujin Qin, Ziyan Zhao, Ying Tang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Just like the assembly line, the disassembly line has a variety of layouts. Selecting a reasonable disassembly line layout according to the disassembly environment is beneficial to improve the disassembly efficiency and reduce the space of the workshop. In order to improve the disassembly efficiency and balance rate, a U-shaped disassembly model is established to maximize disassembly profit and minimize disassembly energy consumption. The model focuses on the harmful risks of dismantling components. Robotic disassembly is the choice for those with higher risks, while manual disassembly is the choice for those with lower risks. In order to solve the balance problem of a U-shaped disassembly line, a multi-objective discrete Bat algorithm is proposed, which can provide a feasible solution for decision- makers. In order to verify the characteristics of the algorithm, we performed comparison with the current popular migratory bird optimization algorithm, artificial bee colony algorithm, non-dominated sorting genetic algorithm, and the decomposition-based multi-objective evolutionary algorithm. The experimental results show that the proposed algorithm is a good chioce to solve this problem. It has a strong search ability.

Original languageEnglish (US)
Title of host publication2021 International Conference on Cyber-Physical Social Intelligence, ICCSI 2021
EditorsJiacun Wang, Ying Tang, Fei-Yue Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665426213
DOIs
StatePublished - 2021
Event2021 International Conference on Cyber-Physical Social Intelligence, ICCSI 2021 - Beijing, China
Duration: Dec 18 2021Dec 20 2021

Publication series

Name2021 International Conference on Cyber-Physical Social Intelligence, ICCSI 2021

Conference

Conference2021 International Conference on Cyber-Physical Social Intelligence, ICCSI 2021
Country/TerritoryChina
CityBeijing
Period12/18/2112/20/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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