SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization

  • Authors:

  • Julian Molina;Manuel Laguna;Rafael Martí;Rafael Caballero

  • Affiliations:

  • Department of Applied Economics (Mathematics), University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain;Leeds School of Business, 419 UCB, University of Colorado, Boulder, Colorado 80309, USA;Department of Statistics and Operational Research, University of Valencia, Dr. Moliner 50, 46100 Burjassot (Valencia), Spain;Department of Applied Economics (Mathematics), University of Málaga, Campus El Ejido s./n., 29071 Málaga, Spain

  • Venue:
  • INFORMS Journal on Computing
  • Year:
  • 2007

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Abstract

We describe the development and testing of a metaheuristic procedure, based on the scatter-search methodology, for the problem of approximating the efficient frontier of nonlinear multiobjective optimization problems with continuous variables. Recent applications of scatter search have shown its merit as a global optimization technique for single-objective problems. However, the application of scatter search to multiobjective optimization problems has not been fully explored in the literature. We test the proposed procedure on a suite of problems that have been used extensively in multiobjective optimization. Additional tests are performed on instances that are an extension of those considered classic. The tests indicate that our adaptation of scatter search is a viable alternative for multiobjective optimization.