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Multi-Objective Job Shop Scheduling Based on Multiagent Evolutionary Algorithm

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Simulated Evolution and Learning (SEAL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6457))

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Abstract

With the properties of multi-objective job shop problem (MOJSP) in mind, we integrate the multiagent systems and evolutionary algorithms to form a new algorithm, multiagent evolutionary algorithm for MOJSP (MAEA-MOJSP). In MAEA-MOJSP, an agent represents a candidate solution to MOJSP, and all agents live in a latticelike environment. Making use of three designed behaviors, the agents sense and interact with their neighbors. In the experiments, eight benchmark problems are used to test the performance of the algorithm proposed. The experimental results show that MAEA-MOJSP is effective.

This work was supported by the National Natural Science Foundation of China under Grant 60872135, 60803098, and 60970067, and the National Research Foundation for the Doctoral Program of Higher Education of China under Grant 20070701022.

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Author information

Authors and Affiliations

  1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, of China, Institute of Intelligent Information Processing, Xidian University, Xi’an, China

    Xinrui Duan, Jing Liu, Li Zhang & Licheng Jiao

Authors
  1. Xinrui Duan
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  2. Jing Liu
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  3. Li Zhang
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  4. Licheng Jiao
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Kalyanmoy Deb

  2. Department of Computer Science andl Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Arnab Bhattacharya

  3. Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, 712302, Kharagpur, West Bengal, India

    Nirupam Chakraborti

  4. Department of Civil Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Partha Chakroborty  & Ashu Jain  & 

  5. Department of Electronics and Communication Engineering, Jadavpur University, 700032, Kolkata, West Bengal, India

    Swagatam Das

  6. Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Joydeep Dutta

  7. Department of Chemical Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Santosh K. Gupta

  8. Aspiring Minds, 24 Pusa Road, 110005, New Delhi, India

    Varun Aggarwal

  9. Warwick Business School, University of Warwick, CV4 7AL, Coventry, UK

    Jürgen Branke

  10. Department of Computer Science and Engineering, University of Nevada, 89557, Reno, NV, USA

    Sushil J. Louis

  11. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore

    Kay Chen Tan

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© 2010 Springer-Verlag Berlin Heidelberg

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Duan, X., Liu, J., Zhang, L., Jiao, L. (2010). Multi-Objective Job Shop Scheduling Based on Multiagent Evolutionary Algorithm. In: Deb, K., et al. Simulated Evolution and Learning. SEAL 2010. Lecture Notes in Computer Science, vol 6457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17298-4_58

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  • DOI: https://doi.org/10.1007/978-3-642-17298-4_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17297-7

  • Online ISBN: 978-3-642-17298-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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