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Evolutionary Scheduling pp 165–195Cite as

An Evolutionary Approach for Solving the Multi-Objective Job-Shop Scheduling Problem

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 49))

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Author information

Authors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong

    Kazi Shah Nawaz Ripon

  2. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong

    Chi-Ho Tsang

  3. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong

    Sam Kwong

Authors
  1. Kazi Shah Nawaz Ripon
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  2. Chi-Ho Tsang
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  3. Sam Kwong
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Editor information

Editors and Affiliations

  1. Modeling Optimisation Scheduling and Intelligent Control (MOSAIC), Research Centre, Department of Computing, University of Bradford, West Yorkshire, BD7 1DP, Bradford, UK

    Keshav P. Dahal

  2. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, Singapore

    Kay Chen Tan

  3. Modeling Optimisation Scheduling and Intelligent Control (MOSAIC), Research Centre, Department of Computing, University of Bradford, West Yorkshire, BD7 1DP, Bradford, UK

    Peter I. Cowling

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Ripon, K.S.N., Tsang, CH., Kwong, S. (2007). An Evolutionary Approach for Solving the Multi-Objective Job-Shop Scheduling Problem. In: Dahal, K.P., Tan, K.C., Cowling, P.I. (eds) Evolutionary Scheduling. Studies in Computational Intelligence, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48584-1_7

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