Titlebook: Meta-Heuristics; Theory and Applicati Ibrahim H. Osman (Programme Chair),James P. Kelly Book 1996 Kluwer Academic Publishers 1996 Optimiza

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Learning to Recognize (Un)Promising Simulated Annealing Runs: Efficient Search Procedures for Job St the expense of intensive computational efforts. The single most significant source of inefficiency in SA search is the inherent stochasticity of the procedure, typically requiring that the procedure be rerun a large number of times before a near-optimal solution is found. This paper describes a me

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A Preliminary Investigation into the Performance of Heuristic Search Methods Applied to Compound Coe overall objective, by means of weightings. Such a problem is therefore . in nature, since its objective is a single entity made up of several individual elements, as with chemical compounds..However, it is reasonable to suppose that compound problems may exhibit different features from truly singl

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Meta-Heuristics: An Overview, biological, mathematical, natural and physical sciences to improve their performance. We shall present brief overviews for the most successful meta-heuristics. The paper concludes with future directions in this growing area of research.

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Evolutionary Computation and Heuristics,g during the reproduction process. However, additional heuristics should be incorporated in the algorithm as well; these heuristic rules provide guidelines for evaluating unfeasible and feasible individuals. This paper surveys such heuristics for discrete and continuous domains and discusses their merits and drawbacks.

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