• ISSN: 2010-0248 (Print)
    • Abbreviated Title: Int. J. Innov.  Manag. Technol.
    • Frequency: Quarterly
    • DOI: 10.18178/IJIMT
    • Editor-in-Chief: Prof. Jin Wang
    • Managing Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Google Scholar, CNKI, Ulrich's Periodicals Directory,  Crossref, Electronic Journals Library.
    • E-mail: ijimt@ejournal.net
HOME > Archive > 2012 > Volume 3 Number 3 (Jun. 2012) >
IJIMT 2012 Vol.3(3): 226-231 ISSN: 2010-0248
DOI: 10.7763/IJIMT.2012.V3.227

Disassembly Sequencing Problems with Stochastic Processing Time using Simplified Swarm Optimization

Wei-Chang Yeh, Chen-Min Lin, and Shang-Chia Wei

Abstract—With eco-awareness and eco-regulation, the end of-life (EOL) disassembly sequencing problem (DSP) has become increasingly important in the process of recycling, reclamation, or remanufacturing EOL products. However, most of the studies in the disassembly sequencing plan assume that the processing time is deterministic for each part’s disassembling procedure. For a realistic and logical approach to the DSP, we take account of the stochastic concept and redefine each part’s disassembling time as an exponentially distributed function. Considering the NP-complete nature of the stochastic problem, this paper presents a revised simplified swarm optimization (SSO) to minimize the total expected disassembling time for the stochastic disassembly sequencing problem (SDSP). The results presented in the study show that the SSO is qualified to effectively schedule the SDSP under limited computation time.

Index Terms—End-of-Life (EOL), exponentially distributed function, simplified swarm optimization (SSO), Precedence Preservative Operator (PPO), stochastic disassembly sequencing problem (SDSP), Group updating mechanism(Group UM).

Authors are with the Department of Industrial Engineering and Engineering Management, National Tsing Hua University (e-mail:yeh@ieee.org).

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Cite: Wei-Chang Yeh, Chen-Min Lin, and Shang-Chia Wei, "Disassembly Sequencing Problems with Stochastic Processing Time using Simplified Swarm Optimization," International Journal of Innovation, Management and Technology vol. 3, no. 3, pp. 226-231 , 2012.

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