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International Conference in Swarm Intelligence

ICSI 2015: Advances in Swarm and Computational Intelligence pp 257–265Cite as

Genetic Algorithm Based Robust Layout Design By Considering Various Demand Variations

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9140))

Abstract

Placement of machines in a limited manufacturing area plays an important role to optimise manufacturing efficiency. Machine layout design (MLD) involves the arrangement of machines into shop floor area to optimise performance measures. The MLD problem is classified as Non-deterministic Polynomial-time hard (NP-hard) problem, in which, the amount of computation required to solve the NP-hard problem increases exponentially with problem size. In the manufacturing context, customers’ demands are periodically varied and therefore have an influence on changing production flow between machines for each time-period. With high variation between periods, the volume of material flow changes significantly. Machine layout can be robustly designed under demand uncertainty over time period so that no machine movement is needed. The objective of this paper was to investigate the effect of five degrees of demand variation on Genetic Algorithm based robust layout design that minimises total material handling distance. The experimental results showed that the degrees of demand variation had significantly affected average material handling distance with 95% confident interval except the largest-size problem. Considering standard deviation, increasing in variability of material handling distance had resulted from the higher degrees of variation especially in the small-size problems. This suggested that designing the robust machine layout should recognise the variation of customer demand.

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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, Phitsanulok, 65000, Thailand

    Srisatja Vitayasak & Pupong Pongcharoen

Authors
  1. Srisatja Vitayasak
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  2. Pupong Pongcharoen
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Corresponding author

Correspondence to Pupong Pongcharoen .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Universidade de Pernambuco, Recife, Brazil

    Fernando Buarque

  4. Instituto Politécnico Nacional, Mexico, Mexico

    Alexander Gelbukh

  5. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  6. University of Pretoria, Pretoria, South Africa

    Andries Engelbrecht

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© 2015 Springer International Publishing Switzerland

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Vitayasak, S., Pongcharoen, P. (2015). Genetic Algorithm Based Robust Layout Design By Considering Various Demand Variations. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9140. Springer, Cham. https://doi.org/10.1007/978-3-319-20466-6_28

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  • DOI: https://doi.org/10.1007/978-3-319-20466-6_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20465-9

  • Online ISBN: 978-3-319-20466-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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