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"Parallel Evolutionary Computation" focuses on the aspects related to the parallelization of evolutionary computations, such as parallel genetic operators, parallel fitness evaluation, distributed genetic algorithms, and parallel hardware implementations, as well as on their impact on several applications. The book is divided into four parts. The first part deals with a clear software-like and algorithmic vision on parallel evolutionary optimizations. The second part is about hardware implementations of genetic algorithms, a valuable topic which is hard to find in the present literature. The third part treats the problem of distributed evolutionary computation and presents three interesting applications wherein parallel EC new ideas are featured. Finally, the last part deals with the up-to-date field of parallel particle swarm optimization to illustrate the intrinsic similarities and potential extensions to techniques in this domain. The book offers a wide spectrum of sample works developed in leading research throughout the world about parallel implementations of efficient techniques at the heart of computational intelligence. It will be useful both for beginners and experienced researchers in the field of computational intelligence.

Evolutionary computation. --- Parallel processing (Electronic computers) --- Réseaux neuronaux à structure évolutive --- Parallélisme (Informatique) --- Engineering. --- Artificial intelligence. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Evolutionary computation --- Computer Science --- Applied Mathematics --- Civil Engineering --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Computation, Evolutionary --- Applied mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Mathematics --- High performance computing --- Multiprocessors --- Parallel programming (Computer science) --- Supercomputers --- Neural networks (Computer science) --- Mathematical and Computational Engineering. --- Artificial Intelligence.

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Evolutionary computation --- Evolutionary programming (Computer science) --- Combinatorial optimization --- Réseaux neuronaux à structure évolutive --- Programmation évolutive --- Optimisation combinatoire --- Congresses. --- Congrès --- Combinatorial optimization -- Congresses. --- Electronic books. -- local. --- Evolutionary computation -- Congresses. --- Evolutionary programming (Computer science) -- Congresses. --- Computer Science --- Engineering & Applied Sciences --- Computer science. --- Computers. --- Algorithms. --- Numerical analysis. --- Computer science --- Computer Science. --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Numeric Computing. --- Discrete Mathematics in Computer Science. --- Mathematics. --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Mathematical analysis --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Informatics --- Science --- Mathematics --- Foundations --- Computer software. --- Electronic data processing. --- Computational complexity. --- Complexity, Computational --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Software, Computer --- Automation --- Computer science—Mathematics. --- Discrete mathematics. --- Theory of Computation. --- Numerical Analysis. --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis

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Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling.

Evolutionary computation. --- Computer scheduling. --- Computational intelligence. --- Réseaux neuronaux à structure évolutive --- Ordonnancement (Informatique) --- Intelligence informatique --- Evolutionary computation --- Computer scheduling --- Computational intelligence --- Applied Mathematics --- Civil Engineering --- Computer Science --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Intelligence, Computational --- Electronic data processing --- Processor scheduling (Electronic data processing) --- Scheduling of electronic data processing --- Computation, Evolutionary --- Scheduling --- Computer science. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Appl.Mathematics/Computational Methods of Engineering. --- Production scheduling --- Time-sharing computer systems --- Neural networks (Computer science) --- Artificial intelligence --- Soft computing --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematics

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This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums, are presented. "Evolutionary Computation in Dynamic and Uncertain Environments" is a valuable reference for scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, natural computing and evolutionary computation.

Evolutionary computation. --- Réseaux neuronaux à structure évolutive --- Evolutionary computation --- Civil Engineering --- Computer Science --- Applied Mathematics --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Computation, Evolutionary --- Engineering. --- Artificial intelligence. --- Statistics. --- Applied mathematics. --- Engineering mathematics. --- Computational intelligence. --- Appl.Mathematics/Computational Methods of Engineering. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Intelligence, Computational --- Artificial intelligence --- Engineering --- Engineering analysis --- Mathematical analysis --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Soft computing --- Neural networks (Computer science) --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Statistics .

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Darwinian evolutionary theory is one of the most important theories in human history for it has equipped us with a valuable tool to understand the amazing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high quality solutions in a large number of domains. EC includes a number of techniques, such as Genetic Algorithms, Genetic Programming, Evolution Strategy and Evolutionary Programming, which have been used in a diverse range of highly successful applications. This book brings together some of these EC applications in fields including electronics, telecommunications, health, bioinformatics, supply chain and other engineering domains, to give the audience, including both EC researchers and practitioners, a glimpse of this exciting rapidly evolving field.

Evolutionary computation. --- Réseaux neuronaux à structure évolutive --- Civil Engineering --- Applied Mathematics --- Computer Science --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Neural networks (Computer science) --- Computation, Evolutionary --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Engineering. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Mathematics --- Artificial intelligence --- Natural computation --- Soft computing --- Mathematical and Computational Engineering. --- Artificial Intelligence.