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of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.;
Vergelijkbare producten zoals Multimodal Optimization by Means of Evolutionary Algorithms
optimization methodology that allows a global search of the cost surface via statistical random processes dictated by the Darwinian evolutionary;
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Classical and Evolutionary Algorithms in the Optimization of Optical Systems presents research results in the field of classical and;
Vergelijkbare producten zoals Classical and Evolutionary Algorithms in the Optimization of Optical Systems
. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty;
Vergelijkbare producten zoals A Brief Introduction to Continuous Evolutionary Optimization
Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single;
Vergelijkbare producten zoals Evolutionary Computation
Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single;
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-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several;
Vergelijkbare producten zoals Meta-heuristic and Evolutionary Algorithms for Engineering Optimization
of evolutionary algorithms to optimization problems. This is complemented by Python source codes, giving users an insight into the idiosyncrasies of the;
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of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All;
Vergelijkbare producten zoals Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms
of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All;
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Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyvaskyla, Finland M. M. Makela;
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Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real--world search and optimization;
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included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary;
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suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators;
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of evolutionary computation. These edited contributions to the Fourth Annual Conference on Evolutionary Programming are by leading scientists from;
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available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that;
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book is an interesting read for engineers, scientists, and students studying/working in the optimization, evolutionary computation, artificial;
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Genetic and Evolutionary Methods is a compendium of articles and papers that were presented at GEM '14, an international conference that;
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emerging EAs and their variants. Chapter 1 introduces the optimization methods in general and the evolutionary algorithms. Chapter 2 presents;
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with a firm grasp of the basic principles of EAs. Covering the theory, history, mathematics, and applications of evolutionary optimization;
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involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting;
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-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering;
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. Evolutionary algorithms are very powerful techniques used to find solutions to real-world search and optimization problems. Many of these problems have;
Vergelijkbare producten zoals Multi-Objective Optimization Using Evolu
papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co;
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, extraction methods for uncertain inference rules by ant colony optimization, a benchmark test suite for evolutionary many-objective optimization, a;
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optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as;
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on Evolutionary Computation (CEC) in 2007, and motivated by the kind invitation made by Dr. Janusz Kacprzyk, I decided to edit a book, with;
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