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Recent Advances in Multiobjective Genetic Algorithms for Manufacturing Scheduling Problems

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Proceedings of the Eighth International Conference on Management Science and Engineering Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 281))

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Abstract

Manufacturing scheduling is one of the important and complex combinatorial optimization problems in manufacturing system, where it can have a major impact on the productivity of a production process. Moreover, most of scheduling problems fall into the class of NP-hard combinatorial problems. In this paper, we concern with the design of multiobjective genetic algorithms (MOGAs) to solve a variety of manufacturing scheduling problems. In particularly, the fitness assignment mechanism and evolutionary representations as well as the hybrid evolutionary operations are introduced. Also, several applications of EAs to the different types of manufacturing scheduling problems are illustrated. Through a variety of numerical experiments, the effectiveness of these hybrid genetic algorithms (HGAs) in the widely applications of manufacturing scheduling problems are demonstrated. This paper also summarizes a classification of scheduling problems and the design way of GAs for the different types of manufacturing scheduling problems in which we apply GAs to a multiobjective flexible job-shop scheduling problem (MoFJSP; operation sequencing with resources assignment) and multiobjective assembly line balancing models (MoALB; shipments grouping and assignment). It is useful to guide how to investigate an effective GA for the practical manufacturing scheduling problems.

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Acknowledgments

This work is partly supported by JSPS: Grant-in-Aid for Scientific Research (C) (No.24510219), Taiwan NSF (NSC 101-2811-E-007-004, NSC 102-2811-E-007-005), the National NSF of China (No. U1304609), the Education Dept. of Henan Province: Basic Research Program of Sci. and Tech. Key Project (No. 13A520203), the Plan of Nature Science Fundamental Research in Henan Univ. of Tech. (No. 2012JCYJ04), the Fundamental Research Funds (Software+X) of Dalian Univ. of Tech. (No.DUT12JR05, No.DUT12JR12) and also the Dongseo Frontier Project Research Fund of Dongseo University.

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Authors and Affiliations

  1. Fuzzy Logic Systems Institute, Lizuka, Japan

    Mitsuo Gen

  2. College of Information Science and Engineering, Henan University of Technology, Zhengzhou, 450000, People’s Republic of China

    Wenqiang Zhang

  3. School of Software Technology, Dalian University of Technology, Dalian, 116000, People’s Republic of China

    Lin Lin

  4. Division of Computer and Information Engineering, Dongseo University, Busan, Korea

    Jungbok Jo

Authors
  1. Mitsuo Gen
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  2. Wenqiang Zhang
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  3. Lin Lin
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  4. Jungbok Jo
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Corresponding author

Correspondence to Mitsuo Gen .

Editor information

Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, China

    Jiuping Xu

  2. Depart de Enge Mecânica e Industrial, Faculdade de Ciências e Tecnologia - Universidade Nova de Lisboa (FCT/UNL), Caparica, Portugal

    Virgílio António Cruz-Machado

  3. LeBow College of Business Department of Decision Sciences, Drexel University, Philadelphia, Pennsylvania, USA

    Benjamin Lev

  4. Institute of Operations Research, Karlsruhe Institute ofTechnology (KIT), Karlsruhe, Germany

    Stefan Nickel

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Gen, M., Zhang, W., Lin, L., Jo, J. (2014). Recent Advances in Multiobjective Genetic Algorithms for Manufacturing Scheduling Problems. In: Xu, J., Cruz-Machado, V., Lev, B., Nickel, S. (eds) Proceedings of the Eighth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55122-2_70

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  • DOI: https://doi.org/10.1007/978-3-642-55122-2_70

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55121-5

  • Online ISBN: 978-3-642-55122-2

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