Parallel Greedy Randomized Adaptive Search Procedures

M.G.C. Resende and C.C. Ribeiro

In Parallel Metaheuristics: A new class of algorithms, E. Alba (ed.), John Wiley and Sons, pp. 315-346, 2005.


A GRASP (Greedy Randomized Adaptive Search Procedure) is a metaheuristic for producing good-quality solutions of combinatorial optimization problems. It is usually implemented with a construction procedure based on  a greedy randomized algorithm followed by local search. In this Chapter, we survey parallel implementations of GRASP. We describe simple strategies to implement independent parallel GRASP heuristics and more complex cooperative schemes using a pool of elite solutions to intensify the search process.  Some applications of independent and cooperative parallelizations are presented in detail.

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