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Applying Ant System for solving Unequal Area Facility Layout Problems

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  • Komarudin
  • Wong, Kuan Yew

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.

Suggested Citation

  • Komarudin & Wong, Kuan Yew, 2010. "Applying Ant System for solving Unequal Area Facility Layout Problems," European Journal of Operational Research, Elsevier, vol. 202(3), pages 730-746, May.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:3:p:730-746
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    2. Liu, Jingfa & Wang, Dawen & He, Kun & Xue, Yu, 2017. "Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1052-1063.
    3. Ali Derakhshan Asl & Kuan Yew Wong & Manoj Kumar Tiwari, 2016. "Unequal-area stochastic facility layout problems: solutions using improved covariance matrix adaptation evolution strategy, particle swarm optimisation, and genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 799-823, February.
    4. Bozer, Yavuz A. & Wang, Chi-Tai, 2012. "A graph-pair representation and MIP-model-based heuristic for the unequal-area facility layout problem," European Journal of Operational Research, Elsevier, vol. 218(2), pages 382-391.
    5. Jerzy Grobelny & Rafal Michalski, 2017. "A novel version of simulated annealing based on linguistic patterns for solving facility layout problems," WORking papers in Management Science (WORMS) WORMS/17/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    6. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2020. "A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 615-640, March.
    7. Paes, Frederico Galaxe & Pessoa, Artur Alves & Vidal, Thibaut, 2017. "A hybrid genetic algorithm with decomposition phases for the Unequal Area Facility Layout Problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 742-756.
    8. Kulturel-Konak, Sadan, 2012. "A linear programming embedded probabilistic tabu search for the unequal-area facility layout problem with flexible bays," European Journal of Operational Research, Elsevier, vol. 223(3), pages 614-625.
    9. Minhee Kim & Junjae Chae, 2019. "Monarch Butterfly Optimization for Facility Layout Design Based on a Single Loop Material Handling Path," Mathematics, MDPI, vol. 7(2), pages 1-21, February.
    10. Gonçalves, José Fernando & Resende, Mauricio G.C., 2015. "A biased random-key genetic algorithm for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 246(1), pages 86-107.
    11. Li, Jinhua & Smith, Alice E., 2018. "Block layout for attraction-based enterprises," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1100-1112.
    12. Jingyang Zhou & Peter E.D. Love & Kok Lay Teo & Hanbin Luo, 2017. "An exact penalty function method for optimising QAP formulation in facility layout problem," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2913-2929, May.
    13. Asef-Vaziri, Ardavan & Jahandideh, Hossein & Modarres, Mohammad, 2017. "Loop-based facility layout design under flexible bay structures," International Journal of Production Economics, Elsevier, vol. 193(C), pages 713-725.

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