Applying Ant System for solving Unequal Area Facility Layout Problems

Komar Komarudin, Kuan Yew Wong

    Research output: Contribution to journalArticlepeer-review

    124 Citations (Scopus)

    Abstract

    Ant Colony Optimization (ACO) is a young metaheuristic algorithm which has shown promising results in solving many optimization problems. To date, a formal ACO-based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This paper proposes an Ant System (AS) (one of the ACO variants) to solve them. As a discrete optimization algorithm, the proposed algorithm uses slicing tree representation to easily represent the problems without too restricting the solution space. It uses several types of local search to improve its search performance. It is then tested using several case problems with different size and setting. Overall, the proposed algorithm shows encouraging results in solving UA-FLPs.
    Original languageEnglish
    Pages (from-to)730-746
    Number of pages17
    JournalEuropean Journal of Operational Research
    Volume202
    Publication statusPublished - 1 May 2010

    Keywords

    • Facility layout
    • Slicing tree representation
    • Ant System
    • Metaheuristic
    • Unequal Area Facility Layout Problem

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