GRASP

Paola Festa () and Mauricio G. C. Resende ()
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Paola Festa: University of Napoli FEDERICO II, Department of Mathematics and Applications “Renato Caccioppoli”
Mauricio G. C. Resende: Amazon.com, Inc. and University of Washington

Chapter 16 in Handbook of Heuristics, 2018, pp 465-488 from Springer

Abstract: Abstract GRASP (greedy randomized adaptive search procedure) is a multistart metaheuristic for computing good-quality solutions of combinatorial optimization problems. Each GRASP iteration is usually made up of a construction phase, where a feasible solution is constructed, and a local search phase which starts at the constructed solution and applies iterative improvement until a locally optimal solution is found. Typically, the construction phase of GRASP is a randomized greedy algorithm, but other types of construction procedures have been also proposed. Repeated applications of a construction procedure yields diverse starting solutions for the local search. This chapter gives an overview of GRASP describing its basic components and enhancements to the basic procedure, including reactive GRASP and intensification strategies.

Keywords: GRASP; Combinatorial optimization; Metaheuristics; Local search; Path-relinking; Hybrid metaheuristics (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-07124-4_23

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DOI: 10.1007/978-3-319-07124-4_23

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