Journal
SWARM AND EVOLUTIONARY COMPUTATION
Volume 57, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.swevo.2020.100719
Keywords
Meta-heuristic; Swarm intelligence; Evolutionary algorithms; Disassembly line balancing; Disassembly planning; Disassembly scheduling
Funding
- National Natural Science Foundation of China [61603169, 61773246, 61773192, 61803192]
- Faculty Research Grants (FRG) from Macau University of Science and Technology [FRG-19-023]
- Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology
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Recently, meta-heuristics have been employed and improved for solving various scheduling and combinational optimization problems. Disassembly line balancing, planning and scheduling problems (DLBPSP) are typical examples since the high complexity (NP-Hard). Since 2000s, numerous articles have represented the applications of meta-heuristics for solving DLBPSP. This paper aims to review the state-of-the-art of this topic. It can help researchers, especially for new researchers, to identify the current status of meta-heuristics for solving DLBPSP, to obtain the technologies used in various algorithms, and to follow the research trends of this topic. First, the related research articles are summarized, classified, and analyzed. Second, the special meta-heuristics for solving DLBPSP are reviewed. The encoding/decoding rules and improvement strategies are analyzed and discussed. Finally, the current research trends are summarized, and some future research directions are given.
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