Greedy randomized adaptive search procedures

L. S. Pitsoulis and M. G. C. Resende

In Handbook of Applied Optimization, P.M. Pardalos and M.G.C. Resende, Eds., Oxford University Press, pp. 168-183, 2002

ABSTRACT

GRASP (greedy randomized adaptive search procedure) is a metaheuristic for combinatorial optimization.  GRASP usually is implemented as a multistart procedure, where each iteration is made up of a construction phase, where a randomized greedy 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.  This chapter gives an overview of GRASP.  Besides describing the basic building blocks of a GRASP, the chapter covers enhancements to the basic procedure, including reactive GRASP, hybrid GRASP, and intensification strategies.

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Last modified: 28 June 2002

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