A Block-based genetic algorithm for disassembly sequence planning. (15th April 2018)

• Record Type: Journal Article
• Authors: Tseng, Hwai-En; Chang, Chien-Cheng; Lee, Shih-Chen; Huang, Yu-Ming
• Is Part Of: Expert systems with applications. Volume 96(2018)
• Page Start: 492
• Page End: 505
• Publication Date: 2018-04-15
• Subjects: Disassembly sequence planning -- Block-based genetic algorithms -- Kongar and Gupta's genetic algorithms -- Dijkstra's algorithms; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2017.11.004
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A block-based genetic algorithm for disassembly sequence planning is proposed. Novel crossover and mutation mechanism are explored. Solution quality is efficient in improving as complexity of problems increase. Abstract: Disassembly sequence planning refers to the study of the sequential order of disassembly based on the limit attributes of parts in the process of disassembly after the product design. The present study proposes a new block-based genetic algorithm for disassembly sequence planning based upon the comparison of Kongar and Gupta's genetic algorithm and Dijkstra's algorithms. It is expected that the disassembly sequence planning problem can be solved more efficiently. Four examples are used to test the algorithms developed in this study. Finally, it shown that the quality of the solution generates met the expected effect.