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A Scatter Search Method for Multiobjective Fuzzy Permutation Flow Shop Scheduling Problem: A Real World Application

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Computational Intelligence in Flow Shop and Job Shop Scheduling

Part of the book series: Studies in Computational Intelligence ((SCI,volume 230))

Summary

In this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).

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Authors and Affiliations

  1. Department of Industrial Engineering, Selçuk University, Konya, Turkey

    Orhan Engin & Mustafa Kerim Yilmaz

  2. Department of Industrial Engineering, İstanbul Technical University, İstanbul, Turkey

    Cengiz Kahraman

Authors
  1. Orhan Engin
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  2. Cengiz Kahraman
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  3. Mustafa Kerim Yilmaz
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Editors and Affiliations

  1. Mathematics & Computer Science Department, University of Missouri, 63121, Saint Louis, MO, USA

    Uday K. Chakraborty

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© 2009 Springer-Verlag Berlin Heidelberg

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Engin, O., Kahraman, C., Yilmaz, M.K. (2009). A Scatter Search Method for Multiobjective Fuzzy Permutation Flow Shop Scheduling Problem: A Real World Application. In: Chakraborty, U.K. (eds) Computational Intelligence in Flow Shop and Job Shop Scheduling. Studies in Computational Intelligence, vol 230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02836-6_6

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  • DOI: https://doi.org/10.1007/978-3-642-02836-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02835-9

  • Online ISBN: 978-3-642-02836-6

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