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Solving constrained multi-objective problems by objective space analysis

Authors:

Gideon Avigad,

Carlos A. Coello CoelloAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 753 - 754

https://doi.org/10.1145/1389095.1389239

Published: 12 July 2008 Publication History

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Abstract

In this paper a new approach to solve constrained multi-objective problems by way of evolutionary multi-objective optimization is introduced. In contrast to former evolutionary approaches, which amalgamate objective space dominance relations with feasibility of solutions considered in the design spaces, the hereby suggested approach relies solely on objective space based analysis. It is shown in this paper that considering the violation of constraints within the design space is problematic as it may lead to misleading conclusions. Moreover, the current approach is inherently capable of dealing with constraints that are imposed directly in the objective space.

References

[1]

Coello Coello, C.A., Theoretical and Numerical Constraint-Handling Techniques used with Evolutionary Algorithms: A Survey of the State of the Art, Computer Methods in Applied Mechanics and Engineering, 191(11-12), pp. 1245--1287, January 2002.]]

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[2]

Jiménez, F. and Verdegay, J.L., Constraint Multiobjective Optimization by Evolutionary Algorithms, Proceedings of the International ICSC Symposium on Engineering of Intelligent Systems (EIS'98), pp:266--271, 1998.]]

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[3]

Deb, K., Pratab, A. and Meyarivan, T., Constrained Test Problems for Multi-objective Evolutionary Optimization, in E. Zitzler et al. (editors), First International Conference on Evolutionary Multi-Criterion Optimization (EMO'01), pp. 284--298, Springer-Verlag, Lecture Notes in Computer Science Vol. 1993, 2001.]]

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Avigad GCoello C(2010)Highly reliable optimal solutions to multi-objective problems and their evolution by means of worst-case analysisEngineering Optimization10.1080/0305215100366815142:12(1095-1117)Online publication date: Dec-2010
https://doi.org/10.1080/03052151003668151
Avigad GMoshaiov A(2009)Interactive evolutionary multiobjective search and optimization of set-based conceptsIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics10.1109/TSMCB.2008.201156539:4(1013-1027)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1109/TSMCB.2008.2011565

Index Terms

Solving constrained multi-objective problems by objective space analysis
1. Applied computing
  1. Arts and humanities
    1. Architecture (buildings)
      1. Computer-aided design
  2. Physical sciences and engineering
    1. Engineering
      1. Computer-aided design
2. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 July 2008

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July 12 - 16, 2008

GA, Atlanta, USA

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Avigad GCoello C(2010)Highly reliable optimal solutions to multi-objective problems and their evolution by means of worst-case analysisEngineering Optimization10.1080/0305215100366815142:12(1095-1117)Online publication date: Dec-2010
https://doi.org/10.1080/03052151003668151
Avigad GMoshaiov A(2009)Interactive evolutionary multiobjective search and optimization of set-based conceptsIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics10.1109/TSMCB.2008.201156539:4(1013-1027)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1109/TSMCB.2008.2011565

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Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms

Ordered Incremental Multi-Objective Problem Solving Based on Genetic Algorithms

A comparative study of constrained multi-objective evolutionary algorithms on constrained multi-objective optimization problems

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