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Use of Infeasible Solutions During Constrained Evolutionary Search: A Short Survey

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Artificial Life and Computational Intelligence (ACALCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9592))

Abstract

Most real world optimization problems involve constraints and constraint handling has long been an area of active research. While older techniques explicitly preferred feasible solutions over infeasible ones, recent studies have uncovered some shortcomings of such strategies. There has been a growing interest in the efficient use of infeasible solutions during the course of search and this paper presents of short review of such techniques. These techniques prefer good infeasible solutions over feasible solutions during the course of search (or a part of it). The review looks at major reported works over the years and outlines how these preferences have been dealt in various stages of the solution process, viz, problem formulation, parent selection/recombination and ranking/selection. A tabular summary is then presented for easy reference to the work in this area.

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Authors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales, Canberra, Australia

    Hemant Kumar Singh, Khairul Alam & Tapabrata Ray

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  1. Hemant Kumar Singh
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  2. Khairul Alam
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  3. Tapabrata Ray
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Correspondence to Hemant Kumar Singh .

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Editors and Affiliations

  1. Canberra, Aust Capital Terr, Australia

    Tapabrata Ray

  2. University of New South Wales, Canberra, Aust Capital Terr, Australia

    Ruhul Sarker

  3. RMIT University, Melbourne, Victoria, Australia

    Xiaodong Li

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Singh, H.K., Alam, K., Ray, T. (2016). Use of Infeasible Solutions During Constrained Evolutionary Search: A Short Survey. In: Ray, T., Sarker, R., Li, X. (eds) Artificial Life and Computational Intelligence. ACALCI 2016. Lecture Notes in Computer Science(), vol 9592. Springer, Cham. https://doi.org/10.1007/978-3-319-28270-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-28270-1_17

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