Effective application of GRASP

P. Festa and M. G. C. Resende 

In Wiley Encyclopedia of Operations Research and Management Sciences,  J.J. Cochran, L.A. Cox, Jr., P. Keskinocak, J.P. Kharoufeh, and J.C. Smith (Eds.), vol. 3,  pp. 1609-1617, Wiley, 2011.


A greedy randomized adaptive search procedure (GRASP) is an iterative multistart metaheuristic for difficult combinatorial optimization. Each {GRASP} iteration consists of two phases: a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Since 1989, GRASP has been applied to a wide range of combinatorial optimization problems, ranging from scheduling and routing to drawing and turbine balancing. In this chapter, we cover the literature where GRASP is applied to scheduling, routing, logic, partitioning, location, graph theory, assignment, manufacturing, transportation, telecommunications, biology and related fields, automatic drawing, power systems, and VLSI design.
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Last modified: 12 February 2011

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