Journal of Global Optimization

, Volume 33, Issue 2, pp 235–255

Experimental Testing of Advanced Scatter Search Designs for Global Optimization of Multimodal Functions

Article

DOI: 10.1007/s10898-004-1936-z

Cite this article as:
Laguna, M. & Martí, R. J Glob Optim (2005) 33: 235. doi:10.1007/s10898-004-1936-z

Abstract

Scatter search is an evolutionary method that, unlike genetic algorithms, operates on a small set of solutions and makes only limited use of randomization as a proxy for diversification when searching for a globally optimal solution. The scatter search framework is flexible, allowing the development of alternative implementations with varying degrees of sophistication. In this paper, we test the merit of several scatter search designs in the context of global optimization of multimodal functions. We compare these designs among themselves and choose one to compare against a well-known genetic algorithm that has been specifically developed for this class of problems. The testing is performed on a set of benchmark multimodal functions with known global minima.

Keywords

scatter search metaheuristic optimization nonlinear optimization 

Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Leeds School of BusinessUniversity of ColoradoBoulderUSA
  2. 2.Departamento de Estadística e Investigación OperativaUniversitat de ValènciaBurjassot (Valencia)Spain

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