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Comparison of Multiple Objective Genetic Algorithms for Parallel Machine Scheduling Problems

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Evolutionary Multi-Criterion Optimization (EMO 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1993))

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Abstract

Many multiple objective genetic algorithms have been developed to approximate the efficient frontier of solutions for multiple objective optimization problems. However, only a limited number of comparison studies have been performed on practical problems. One of the reasons for this may be the lack of commonly accepted measures to compare the solution quality of sets of approximately optimal solutions. In this paper, we perform an extensive set of experiments to quantitatively compare the solutions of two competing algorithms for a bi-criteria parallel machine-scheduling problem.

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Author information

Authors and Affiliations

  1. Industrial Engineering, Arizona State University, AZ 85287, P.O. Box 855906, Tempe

    W. Matthew Carlyle, Bosun Kim, John W. Fowler & Esma S. Gel

Authors
  1. W. Matthew Carlyle
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  2. Bosun Kim
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  3. John W. Fowler
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  4. Esma S. Gel
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, ETH Zentrum, Gloriastrasse 35, 8092, Zurich, Switzerland

    Eckart Zitzler  & Lothar Thiele  & 

  2. Department of Mechanical Engineering Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology, UP 208 016, Kanpur, India

    Kalyanmoy Deb

  3. Electrical Engineering Department,Computer Science Section Av.Instituto Politecnico Nacional No.2508, CINVESTAV-IPN, Col.San Pedro Zacatenco, 07300, Mexico City, Mexico

    Carlos Artemio Coello Coello

  4. Department of Computer Science, University of Reading, P.O.Box 225, Reading RG6 6AY, Whiteknights, UK

    David Corne

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© 2001 Springer-Verlag Berlin Heidelberg

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Matthew Carlyle, W., Kim, B., Fowler, J.W., Gel, E.S. (2001). Comparison of Multiple Objective Genetic Algorithms for Parallel Machine Scheduling Problems. In: Zitzler, E., Thiele, L., Deb, K., Coello Coello, C.A., Corne, D. (eds) Evolutionary Multi-Criterion Optimization. EMO 2001. Lecture Notes in Computer Science, vol 1993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44719-9_33

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  • DOI: https://doi.org/10.1007/3-540-44719-9_33

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41745-3

  • Online ISBN: 978-3-540-44719-1

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