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Pareto set approximation by the method of adjustable weights and successive lexicographic goal programming

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Abstract

A nonlinear multiobjective optimization problem is considered. Two methods are proposed to generate solutions with an approximately uniform distribution in a Pareto set. The first method is supposed to find the solutions as minimizers of weighted sums of objective functions where the weights are properly selected using a branch and bound type algorithm. The second method is based on lexicographic goal programming. The proposed methods are compared with several metaheuristic methods using two and three-criteria tests and applied problems.

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Authors and Affiliations

  1. University of Florida, 303 Weil Hall, Gainesville, FL, 32611, USA

    Panos M. Pardalos

  2. Vytautas Magnus University, Vileikos str. 8, 44404, Kaunas, Lithuania

    Ingrida Steponavičė

  3. Institute of Mathematics and Informatics, Vilnius University, Akademijos str. 4, 08663, Vilnius, Lithuania

    Antanas Z̆ilinskas

Authors
  1. Panos M. Pardalos
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  2. Ingrida Steponavičė
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  3. Antanas Z̆ilinskas
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Correspondence to Ingrida Steponavičė.

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Pardalos, P.M., Steponavičė, I. & Z̆ilinskas, A. Pareto set approximation by the method of adjustable weights and successive lexicographic goal programming. Optim Lett 6, 665–678 (2012). https://doi.org/10.1007/s11590-011-0291-5

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  • DOI: https://doi.org/10.1007/s11590-011-0291-5

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