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A Population and Interval Constraint Propagation Algorithm

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Evolutionary Multi-Criterion Optimization (EMO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2632))

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Abstract

We present PICPA, a new algorithm for tackling constrained continuous multi-objective problems. The algorithm combines constraint propagation techniques and evolutionary concepts. Unlike other evolutionary algorithm which gives only heuristic solutions, PICPA is able to bound effectively the Pareto optimal front as well as to produce accurate approximate solutions.

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Author information

Authors and Affiliations

  1. LERIA - Faculty of Sciences, University of Angers, 2, Boulevard Lavoisier, 49045, Angers Cedex 01, France

    Vincent Barichard & Jin-Kao Hao

Authors
  1. Vincent Barichard
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  2. Jin-Kao Hao
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Editor information

Editors and Affiliations

  1. Faculty of Sciences and Technology, Centre for Intelligent Systems, University of the Algarve, Campus de Gambelas, 8005-139, Faro, Portugal

    Carlos M. Fonseca

  2. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK

    Peter J. Fleming

  3. Department of Electrical Engineering, Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, Gloriastraße 35, 8092, Zürich, Switzerland

    Eckart Zitzler  & Lothar Thiele  & 

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

    Kalyanmoy Deb

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© 2003 Springer-Verlag Berlin Heidelberg

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Barichard, V., Hao, JK. (2003). A Population and Interval Constraint Propagation Algorithm. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Thiele, L., Deb, K. (eds) Evolutionary Multi-Criterion Optimization. EMO 2003. Lecture Notes in Computer Science, vol 2632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36970-8_7

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  • DOI: https://doi.org/10.1007/3-540-36970-8_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-01869-8

  • Online ISBN: 978-3-540-36970-7

  • eBook Packages: Springer Book Archive

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