Titlebook: Matheuristics; Algorithms and Imple Vittorio Maniezzo,Marco Antonio Boschetti,Thomas S Textbook 2021 The Editor(s) (if applicable) and The

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Automatic Design for Matheuristicsact, in this book we have many such methods, ranging from metaheuristics and mathematical programming techniques but mainly to real matheuristics. In these methods we will see no parameter settings, but it is true: all these methods in the end rely on a good parameter setting. Here, in this chapter,

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Single Solution Metaheuristicsgorithm: one single solution or more than one. This chapter deals with metaheuristic algorithms that evolve one single solution; they are all enhancements of a basic local search procedure. Many different approaches have been presented, which could be included here. We choose six of them, namely Sim

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Population-Based Metaheuristicsts of candidate solutions, often named “.” of solutions. Genetic algorithms were among the first results, and following their success it became common to get inspiration from some natural phenomenon to design the heuristic. This chapter considers three representative population-evolving metaheuristi

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staging

Corridor Methoder, it has been extended beyond DP to other exact optimization methods. The basic idea is that of using the exact method over successive restricted portions of the solution space of the given problem. The restriction is obtained by applying exogenous constraints, which define local neighborhoods aro

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Kernel Search (mixed) integer linear programming problems. It was first presented as a method to solve mixed-integer linear problems defined on binary variables modeling items selection, together with other integer or continuous variables related to the selected items, and later extended also to problems that do

Oration

Fore-and-Backnes), is an extension of . that can improve its effectiveness and that, when run with no limits on computational resources, becomes an exact solution method. However, by design, Fore-and-Back is mainly concerned with heuristic solving, trying to quickly get high quality solutions with little attenti

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