Greedy Randomized Adaptive Search Procedures
نویسنده
چکیده
GRASP is an iterative multi-start metaheuristic for solving difficult combinatorial problems. Each GRASP iteration consists of two phases: a greedy adaptive randomized construction phase and a local search phase. Starting from the feasible solution built during the greedy adaptive randomized construction phase, the local search explores its neighborhood until a local optimum is found. The best solution found overall the different iterations is kept as the result. In this paper, the basic components of GRASP are described in detail. Successful implementations are discussed together with improved and alternative solution construction mechanisms as well as techniques proposed in literature for speeding up the search, hybridizations with other metaheuristics, and intensification and post-optimization strategies using pathrelinking.
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