Solving facility layout problem via particle Swarm optimization

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

    9 Citations (Scopus)

    Abstract

    This paper targets the Facility Layout Problem (FLP), which has many practical applications and known to be NP-hard. During recent decades, a number of algorithms have been proposed to solve this problem. Most of those algorithms try to solve this problem by encoding layout candidates and using combinational optimization techniques to obtain the best one among those encoded candidates. However, since there exist layouts which cannot be represented by those encoding techniques, there is possibility of missing the searching opportunity for the optimal solution. To overcome this problem, this paper is concerned with the development of algorithm to solve FLP by searching continuously optimal coordinate of each department. In particular, this paper proposes an algorithm solving FLP via Particle Swarm Optimization (PSO), which is known to be effective for many types of continuous optimization problem.

    Original languageEnglish
    Title of host publication3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice
    Pages409-413
    Number of pages5
    Volume1
    DOIs
    Publication statusPublished - 2010
    Event3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice - Huangshan, Anhui
    Duration: 2010 May 282010 May 31

    Other

    Other3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice
    CityHuangshan, Anhui
    Period10/5/2810/5/31

    Fingerprint

    Facility Layout
    Particle swarm optimization (PSO)
    Particle Swarm Optimization
    Layout
    Encoding
    Continuous Optimization
    Optimization Techniques
    NP-complete problem
    Optimal Solution
    Optimization Problem
    Target

    Keywords

    • Layout
    • PSO

    ASJC Scopus subject areas

    • Control and Optimization
    • Computational Theory and Mathematics
    • Computer Science Applications
    • Theoretical Computer Science

    Cite this

    Ohmori, S., Yoshimoto, K., & Ogawa, K. (2010). Solving facility layout problem via particle Swarm optimization. In 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice (Vol. 1, pp. 409-413). [5533062] https://doi.org/10.1109/CSO.2010.242

    Solving facility layout problem via particle Swarm optimization. / Ohmori, Shunichi; Yoshimoto, Kazuho; Ogawa, Kenshu.

    3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice. Vol. 1 2010. p. 409-413 5533062.

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

    Ohmori, S, Yoshimoto, K & Ogawa, K 2010, Solving facility layout problem via particle Swarm optimization. in 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice. vol. 1, 5533062, pp. 409-413, 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice, Huangshan, Anhui, 10/5/28. https://doi.org/10.1109/CSO.2010.242
    Ohmori S, Yoshimoto K, Ogawa K. Solving facility layout problem via particle Swarm optimization. In 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice. Vol. 1. 2010. p. 409-413. 5533062 https://doi.org/10.1109/CSO.2010.242
    Ohmori, Shunichi ; Yoshimoto, Kazuho ; Ogawa, Kenshu. / Solving facility layout problem via particle Swarm optimization. 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice. Vol. 1 2010. pp. 409-413
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