On Gradient-Based Local Search to Hybridize Multi-objective Evolutionary Algorithms View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Adriana Lara , Oliver Schütze , Carlos A. Coello Coello

ABSTRACT

Using evolutionary algorithms when solving multi-objective optimization problems (MOPs) has shown remarkable results during the last decade. As a consolidated research area it counts with a number of guidelines and processes; even though, their efficiency is still a big issue which lets room for improvements. In this chapter we explore the use of gradient-based information to increase efficiency on evolutionary methods, when dealing with smooth real-valued MOPs. We show the main aspects to be considered when building local search operators using the objective function gradients, and when coupling them with evolutionary algorithms. We present an overview of our current methods with discussion about their convenience for particular kinds of problems. More... »

PAGES

305-332

References to SciGraph publications

  • 2003-06-18. Effective Use of Directional Information in Multi-objective Evolutionary Computation in GENETIC AND EVOLUTIONARY COMPUTATION — GECCO 2003
  • 2005. The Naive IDA: A Baseline Multi–objective EA in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • 2001. Nonlinear Multiobjective Optimization, A Generalized Homotopy Approach in NONE
  • 2008. A Local Search Based Evolutionary Multi-objective Optimization Approach for Fast and Accurate Convergence in PARALLEL PROBLEM SOLVING FROM NATURE – PPSN X
  • 2002-07. Stochastic Method for the Solution of Unconstrained Vector Optimization Problems in JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
  • 2000-08. Steepest descent methods for multicriteria optimization in MATHEMATICAL METHODS OF OPERATIONS RESEARCH
  • 2007. Gradient Based Stochastic Mutation Operators in Evolutionary Multi-objective Optimization in ADAPTIVE AND NATURAL COMPUTING ALGORITHMS
  • 2006. About Selecting the Personal Best in Multi-Objective Particle Swarm Optimization in PARALLEL PROBLEM SOLVING FROM NATURE - PPSN IX
  • 2005-01. Covering Pareto Sets by Multilevel Subdivision Techniques in JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
  • 2007. On Gradient Based Local Search Methods in Unconstrained Evolutionary Multi-objective Optimization in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • Book

    TITLE

    EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation

    ISBN

    978-3-642-32725-4
    978-3-642-32726-1

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-32726-1_9

    DOI

    http://dx.doi.org/10.1007/978-3-642-32726-1_9

    DIMENSIONS

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