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Computational Intelligence in Optimization pp 177–209Cite as

A Review of Agent-Based Co-Evolutionary Algorithms for Multi-Objective Optimization

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Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 7))

Abstract

Agent-based evolutionary algorithms are a result of mixing two paradigms: multi-agent systems and evolutionary algorithms. Agent-based co-evolutionary algorithms allow for existing many species and sexes of agents within the system as well as for defining co-evolutionary interactions between species and sexes. Algorithms based on the model of co-evolutionary multi-agent system have been already applied in many domains, like multi-modal optimization, generation of investment strategies, portfolio optimization, and multi-objective optimization. In this chapter we present an overview of selected agent-based co-evolutionary algorithms, their formal models, and results of experiments with standard test problems and financial problem, aimed at making comparison of agent-based and “classical” state-of-the-art multi-objective algorithms. Presented results show that, depending on the problem being solved, agent-based algorithms obtain comparable, and sometimes even better, results than “classical” algorithms, however of course they are not the universal solver for all multi-objective optimization problems.

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Authors and Affiliations

  1. Department of Computer Science, AGH University of Science and Technology, Kraków, Poland

    Rafał Dreżewski & Leszek Siwik

Authors
  1. Rafał Dreżewski
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  2. Leszek Siwik
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering and Science-Faculty of Engineering, Kyoto University, Yoshida-honmachi,Sakyo-Ku, 606-8501, Kyoto, Japan

    Yoel Tenne

  2. Advanced Technology Centre, Rolls-Royce Singapore Pte Ltd, 50 Nanyang Avenue, Block N2,Level B3C,Unit 05-08, 639798, Singapore

    Chi-Keong Goh

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Dreżewski, R., Siwik, L. (2010). A Review of Agent-Based Co-Evolutionary Algorithms for Multi-Objective Optimization. In: Tenne, Y., Goh, CK. (eds) Computational Intelligence in Optimization. Adaptation, Learning, and Optimization, vol 7. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12775-5_8

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  • DOI: https://doi.org/10.1007/978-3-642-12775-5_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12774-8

  • Online ISBN: 978-3-642-12775-5

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