An efficient hybrid artificial bee colony algorithm for disassembly line balancing problem with sequence-dependent part removal times. Issue 11 (2nd November 2019)

• Record Type: Journal Article
• Authors: Wang, Shuwei; Guo, Xiuping; Liu, Jia
• Is Part Of: Engineering optimization. Volume 51:Issue 11(2019)
• Page Start: 1920
• Page End: 1937
• Publication Date: 2019-11-02
• Subjects: Disassembly -- sequence-dependent disassembly line balancing -- artificial bee colony algorithm -- dynamic neighbourhood search; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2018.1564918
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This study deals with a sequence-dependent disassembly line balancing problem by considering the interactions among disassembly tasks, and a multi-objective mathematical model is established. Subsequently, a novel hybrid artificial bee colony algorithm is proposed to solve the problem. A new rule is used to initialize a bee colony population with certain diversity, and a dynamic neighbourhood search method is introduced to guide the employed/onlooker bees to promising regions. To rapidly leave the local optima, a global learning strategy is employed to explore higher quality solutions. In addition, a multi-stage evaluation method is designed for onlookers to effectively select employed bees to follow. The performance of the proposed algorithm is tested on a set of benchmark instances and two case scenarios, and the results are compared with several other metaheuristics in terms of solution quality and computation time. The comparisons demonstrate that the proposed algorithm exhibits superior performance.