Applying Ant System for solving Unequal Area Facility Layout Problems

Komarudin, Kuan Yew Wong

Research output: Contribution to journalArticlepeer-review

122 Citations (Scopus)


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
Issue number3
Publication statusPublished - 1 May 2010


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


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