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Titlebook: Optimization by GRASP; Greedy Randomized Ad Mauricio G.C. Resende,Celso C. Ribeiro Textbook 2016 Springer Science+Business Media New York 2

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A short tour of combinatorial optimization and computational complexity,ms, polynomial-time algorithms, and .-complete problems. The chapter concludes with a discussion of solution approaches for .-hard problems, introducing constructive heuristics, local search or improvement procedures and, finally, metaheuristics.
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Parallel GRASP heuristics,rocessors sharing and exchanging information about elite solutions visited during the GRASP iterations. This chapter is an introduction to parallel GRASP heuristics, covering multiple-walk independent-thread strategies, multiple-walk cooperative-thread strategies, and some applications of parallel GRASP and parallel GRASP with path-relinking.
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Local search,he definition of a neighborhood by a number of examples for different problems. Local search methods are introduced and different implementation issues are discussed, such as neighborhood search strategies, quick cost updates, and candidate list strategies.
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Extended construction heuristics,ions, bias functions, principles of intelligent construction based on memory and learning, the proximate optimality principle and local search applied to partially constructed solutions, and pattern-based construction strategies using vocabulary building or data mining.
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GRASP with path-relinking,olution resulting from path-relinking is a candidate for inclusion in the elite set. In this chapter we examine elite sets, their integration with GRASP, the basic GRASP with path-relinking procedure, several variants of the basic scheme, including evolutionary path-relinking, and restart strategies for GRASP with path-relinking heuristics.
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GRASP for continuous optimization,te locally optimal solution. A deterministic rule triggers a restart after each C-GRASP iteration. This chapter addresses the construction phase and the restart strategy, and presents a local search procedure for continuous GRASP.
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