Standard Article

Grasp: Greedy Randomized Adaptive Search Procedures

  1. Mauricio G. C. Resende1,
  2. Ricardo M. A. Silva2

Published Online: 15 FEB 2011

DOI: 10.1002/9780470400531.eorms0367

Wiley Encyclopedia of Operations Research and Management Science

Wiley Encyclopedia of Operations Research and Management Science

How to Cite

Resende, M. G. C. and Silva, R. M. A. 2011. Grasp: Greedy Randomized Adaptive Search Procedures. Wiley Encyclopedia of Operations Research and Management Science. .

Author Information

  1. 1

    AT&T Labs Research, Algorithms and Optimization Research Department, Florham Park, New Jersey

  2. 2

    Federal University of Lavras, Computational Intelligence and Optimization Group, Department of Computer Science, Lavras, Brazil

Publication History

  1. Published Online: 15 FEB 2011

Abstract

GRASP or greedy randomized adaptive search procedure, is a multistart metaheuristic that repeatedly applies local search starting from solutions constructed by a randomized greedy algorithm. In this article we review the basic building blocks of GRASP. We cover solution construction schemes, local search methods, and the use of path-relinking as a memory mechanism in GRASP.

Keywords:

  • GRASP;
  • metaheuristics;
  • hybrid heuristics;
  • path-relinking;
  • local search