Increasing selective pressure towards the best compromise in evolutionary multiobjective optimization: The extended NOSGA method

  • Authors:

  • Eduardo Fernandez;Edy Lopez;Fernando Lopez;Carlos A. Coello Coello

  • Affiliations:

  • Autonomous University of Sinaloa, Facultad de Ingenieria, Ciudad Universitaria, Culiacan, CP 80040, Mexico;Autonomous University of Sinaloa, Facultad de Ingenieria, Ciudad Universitaria, Culiacan, CP 80040, Mexico;Autonomous University of Sinaloa, Facultad de Ingenieria, Ciudad Universitaria, Culiacan, CP 80040, Mexico;Autonomous University of Sinaloa, Facultad de Ingenieria, Ciudad Universitaria, Culiacan, CP 80040, Mexico

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2011

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Abstract

Most current approaches in the evolutionary multiobjective optimization literature concentrate on adapting an evolutionary algorithm to generate an approximation of the Pareto frontier. However, finding this set does not solve the problem. The decision-maker still has to choose the best compromise solution out of that set. Here, we introduce a new characterization of the best compromise solution of a multiobjective optimization problem. By using a relational system of preferences based on a multicriteria decision aid way of thinking, and an outranked-based dominance generalization, we derive some necessary and sufficient conditions which describe satisfactory approximations to the best compromise. Such conditions define a lexicographic minimum of a bi-objective optimization problem, which is a map of the original one. The NOSGA-II method is a NSGA-II inspired efficient way of solving the resulting mapped problem.