Standard Article

The Scatter Search Methodology

  1. Manuel Laguna1,
  2. Rafael Martí2,
  3. Micael Gallego3,
  4. Abraham Duarte3

Published Online: 14 JAN 2011

DOI: 10.1002/9780470400531.eorms0284

Wiley Encyclopedia of Operations Research and Management Science

Wiley Encyclopedia of Operations Research and Management Science

How to Cite

Laguna, M., Martí, R., Gallego, M. and Duarte, A. 2011. The Scatter Search Methodology. Wiley Encyclopedia of Operations Research and Management Science. .

Author Information

  1. 1

    University of Colorado at Boulder, Leeds School of Business

  2. 2

    Universidad de Valencia, Departamento de Estadística e Investigación Operativa, Spain

  3. 3

    Universidad Rey Juan Carlos, Departamento de Ciencias de la Computación, Spain

Publication History

  1. Published Online: 14 JAN 2011

Abstract

Scatter search (SS) is an evolutionary approach for optimization. It has been applied to problems with continuous and discrete variables and with a single or multiple objectives. The success of SS as an optimization technique is well documented in a constantly growing number of journal articles and book chapters. This article first focuses on the basic SS framework, which is responsible for most of the outcomes reported in the literature, and then covers advanced elements that have been introduced in a few selected papers, such as the hybridization with tabu search, a well-known memory-based metaheuristic. We consider the maximum diversity problem to illustrate the search elements, methods and strategies described here.

Keywords:

  • tabu search;
  • scatter search;
  • maximum diversity problem