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Titlebook: Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach; First International José Mira,José R. Álvarez Conf

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https://doi.org/10.1007/978-3-662-69492-3In the sequel we shall consider the ., a variation of the job-shop problem where the duration of tasks may be uncertain and where due-date constraints are flexible. Our aim is to provide a semantics for this problem and fix some criteria to analyse solutions obtained by Evolutionary Algorithms.
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An Evolutionary Approach to Designing and Solving Fuzzy Job-Shop ProblemsIn the sequel we shall consider the ., a variation of the job-shop problem where the duration of tasks may be uncertain and where due-date constraints are flexible. Our aim is to provide a semantics for this problem and fix some criteria to analyse solutions obtained by Evolutionary Algorithms.
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Tamta Margvelashvili,Solomon Bagashvilidification schemas for the Job Shop Scheduling problem which are extensions of two schemas of common use, and are worked out from the concept of underlying probabilistic model. Someway the underlying probabilistic model of a codification schema accounts for a tendency of the schema to represent solu
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Hoang Thai Hy Nguyen,Thị Thuy Duong Tranarch. It is a population-based metaheuristic founded on a formulation proposed two decades ago by Fred Glover. It uses linear combinations on a population subsets to create new solutions while other evolutionary approaches like genetic algorithms resort to randomization. First, we implement the proc
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https://doi.org/10.1007/978-3-7091-6119-7e to the optimum. This novel method for Blindly Separating unobservable independent component Sources (BSS) consists of novel guiding genetic operators (GGA) and finds the separation matrix which minimizes a contrast function. The convergence is shown under little restrictive conditions for the guid
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https://doi.org/10.1007/978-3-662-69492-3metic algorithms (MAs) for solving this problem. A specialized local-improvement operator based on character removal and heuristic repairing plays a central role in the MA. The tradeoff between the improvement achieved by this operator and its computational cost is analyzed. Empirical results indica
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