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Titlebook: Handbook of Metaheuristics; Michel Gendreau,Jean-Yves Potvin Book 2019Latest edition Springer International Publishing AG, part of Springe

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樓主: Detrusor-Muscle
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發(fā)表于 2025-3-23 10:06:52 | 只看該作者
International Series in Operations Research & Management Sciencehttp://image.papertrans.cn/h/image/421651.jpg
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發(fā)表于 2025-3-23 16:46:32 | 只看該作者
Simulated Annealing: From Basics to Applications,ctive function is not explicitly given and can only be evaluated via some costly computer simulation. It is massively used in real-life applications. The main advantage of SA is its simplicity. SA is based on an analogy with the physical annealing of materials that avoids the drawback of the Monte-C
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發(fā)表于 2025-3-23 20:43:51 | 只看該作者
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發(fā)表于 2025-3-24 00:22:31 | 只看該作者
Variable Neighborhood Search,ge of neighborhood both within a descent phase to find a local optimum and in a perturbation phase to get out of the corresponding valley. In this chapter we present the basic schemes of VNS and some of its extensions. We then describe recent developments, i.e., formulation space search and variable
15#
發(fā)表于 2025-3-24 03:04:14 | 只看該作者
Large Neighborhood Search,portation and scheduling problems. Large neighborhood search methods explore a complex neighborhood through the use of heuristics. Using large neighborhoods makes it possible to find better candidate solutions in each iteration and hence follow a more promising search path. Starting from the general
16#
發(fā)表于 2025-3-24 07:55:03 | 只看該作者
Iterated Local Search: Framework and Applications,turned by some underlying algorithm, typically a local search heuristic. The resulting search behavior can be characterized as iteratively building a chain of solutions of this embedded algorithm. The result is also a conceptually simple metaheuristic that nevertheless has led to state-of-the-art al
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發(fā)表于 2025-3-24 13:23:23 | 只看該作者
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發(fā)表于 2025-3-24 16:23:04 | 只看該作者
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發(fā)表于 2025-3-24 22:12:52 | 只看該作者
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發(fā)表于 2025-3-24 23:18:28 | 只看該作者
An Accelerated Introduction to Memetic Algorithms,itation of specific problem knowledge as one of their guiding principles. In its most classical form, a MA is typically composed of an underlying population-based engine onto which a local search component is integrated. These aspects are described in this chapter in some detail, paying particular a
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