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Bat Algorithm, Genetic Algorithm and Shuffled Frog Leaping Algorithm for Designing Machine Layout

  • Conference paper
Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8271))

Abstract

Arranging non-identical machines into a limited area of manufacturing shop floor is an essential part of plant design. Material handling distance is one of the key performance indexes of internal logistic activities within manufacturing companies. It leads to the efficient productivity and related costs. Machine layout design is known as facility layout problem and classified into non-deterministic polynomial-time hard problem. The objective of this paper was to compare the performance of Bat Algorithm (BA), Genetic Algorithm (GA) and Shuffled Frog Leaping Algorithm (SFLA) for designing machine layouts in a multiple-row environment with the aim to minimise the total material handling distance. An automated machine layout design tool has been coded in modular style using a general purpose programming language called Tcl/Tk. The computational experiment was designed and conducted using four MLD benchmark datasets adopted from literature. It was found that the proposed algorithms performed well in different aspects.

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Author information

Authors and Affiliations

  1. Centre of Operations Research and Industrial Applications, Department of Industrial Engineering, Faculty of Engineering, Naresuan University, 65000, Phitsanulok, Thailand

    Kittipong Dapa, Pornpat Loreungthup, Srisatja Vitayasak & Pupong Pongcharoen

Authors
  1. Kittipong Dapa
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  2. Pornpat Loreungthup
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  3. Srisatja Vitayasak
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  4. Pupong Pongcharoen
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Editor information

Editors and Affiliations

  1. Department of Applied Computer Science, University of Winnipeg, R3B 2E9, Winnipeg, Manitoba, Canada

    Sheela Ramanna

  2. Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, Nova Scotia, Canada

    Pawan Lingras

  3. Faculty of Informatics, Mahasarakham University, Khamreang, 44150, Kantarawichai, Mahasarakham, Thailand

    Chattrakul Sombattheera

  4. Department of Computing, Curtin University, Perth, WA, Australia

    Aneesh Krishna

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© 2013 Springer-Verlag Berlin Heidelberg

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Dapa, K., Loreungthup, P., Vitayasak, S., Pongcharoen, P. (2013). Bat Algorithm, Genetic Algorithm and Shuffled Frog Leaping Algorithm for Designing Machine Layout. In: Ramanna, S., Lingras, P., Sombattheera, C., Krishna, A. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2013. Lecture Notes in Computer Science(), vol 8271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44949-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-44949-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-44948-2

  • Online ISBN: 978-3-642-44949-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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