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Titlebook: Evolutionary Programming VI; 6th International Co Peter J. Angeline,Robert G. Reynolds,Russ Eberhart Conference proceedings 1997 Springer-V

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https://doi.org/10.1057/9780230288980 discontinuous. Although recombination operators have been introduced into evolution strategies, their primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations. A new mutation operator based on the Cauchy distribution is proposed in this paper. It is shown
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Robin Williams,Wendy Faulkner,James Fleckted route and slot of departure. For each flight a set of alternative routes and a set of possible slots of departure are defined. One must find “optimal” route and slot allocation for each aircraft in a way that significantly reduces the peak of workload in the most congested sectors and in the mos
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Franklin Santana Santos,Peter Fenwick (1) a multi-phase optimization process and (2) constraint scaling techniques to resolve problem of ill-conditioning. In each phase of Evolian, the typical evolutionary programming (EP) is performed using an augmented Lagrangian objective function with a penalty parameter fixed. If there is no impro
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Crafting Meaningful Experiences,hat quickly finds solutions to static and dynamic Fuzzy Constraint Truth Optimization Problems (FCTOPs). We compare the static and dynamic methods for solving FCTOPs using a test suite of an additional 250 randomly generated FCTOPs. In the static method, all the constraints of a FCTOP are known by t
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Amelia F. Underwood,Debra J. Dean Evolution Strategy (FCES) can be viewed as a local competition involving the children generated from the same parent, while the selection is a global competition among all of the members in the population. According to our experimental results, the self-adaptation of strategy parameters with determ
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Martin Bohle,Giuseppe Di Capua,Nic Bilhame as the primary operator leads to faster convergence for certain function optimization problems. In this study we explore the use of both the Gaussian and the Cauchy operators along with a self-adaptive mechanism to select the appropriate operator for each individual in the population. Empirical st
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https://doi.org/10.1057/978-1-137-59688-8per explores the benefits of using polyploidy in Genetic Algorithms. Polyploidy is provided in our approach by using a local chromosome to reflect dominance in diploid and tetraploid organisms, with and without evolving crossover points, added to provide linkage between chromosomes and the dominance
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/318009.jpg
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https://doi.org/10.1057/9781137449405ce Computing Environment. PEPNet, Parallel EPNet, implements four forms of parallelism and this paper describes two of those parallelisms. Experimental studies have shown promising results with better time and prediction performance.
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