Evolutionary Many-Objective Optimization Based on Kuhn-Munkres’ Algorithm View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

José A. Molinet Berenguer , Carlos A. Coello Coello

ABSTRACT

In this paper, we propose a new multi-objective evolutionary algorithm (MOEA), which transforms a multi-objective optimization problem into a linear assignment problem using a set of weight vectors uniformly scattered. Our approach adopts uniform design to obtain the set of weights and Kuhn-Munkres’ (Hungarian) algorithm to solve the assignment problem. Differential evolution is used as our search engine, giving rise to the so-called Hungarian Differential Evolution algorithm (HDE). Our proposed approach is compared with respect to a MOEA based on decomposition (MOEA/D) and with respect to an indicator-based MOEA (the S metric selection Evolutionary Multi-Objective Algorithm, SMS- EMOA) using several test problems (taken from the specialized literature) having from two to ten objective functions. Our preliminary experimental results indicate that our proposed HDE outperforms MOEA/D and is competitive with respect to SMS-EMOA, but at a significantly lower computational cost. More... »

PAGES

3-17

References to SciGraph publications

  • 2008. Analyzing Hypervolume Indicator Based Algorithms in PARALLEL PROBLEM SOLVING FROM NATURE – PPSN X
  • 2003. The Measure of Pareto Optima Applications to Multi-objective Metaheuristics in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • 2005. Scalable Test Problems for Evolutionary Multiobjective Optimization in EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION
  • 2004. Indicator-Based Selection in Multiobjective Search in PARALLEL PROBLEM SOLVING FROM NATURE - PPSN VIII
  • Book

    TITLE

    Evolutionary Multi-Criterion Optimization

    ISBN

    978-3-319-15891-4
    978-3-319-15892-1

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-15892-1_1

    DOI

    http://dx.doi.org/10.1007/978-3-319-15892-1_1

    DIMENSIONS

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