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In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has focused on operators and test problems, while problem representation has often been taken as given. This book breaks away from this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-to-read style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.

Genetic programming (Computer science) --- Genetic algorithms. --- Evolutionary programming (Computer science) --- Representations of groups. --- Representations of algebras. --- Algebra --- Group representation (Mathematics) --- Groups, Representation theory of --- Group theory --- Computer programming --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Algorithms --- Combinatorial optimization --- Evolutionary computation --- Learning classifier systems --- Genetic algorithms --- Engineering mathematics. --- Artificial intelligence. --- Operations research. --- Information technology. --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Operations Research/Decision Theory. --- IT in Business. --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- 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 --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Applied mathematics. --- Decision making. --- Business—Data processing. --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Decision making

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The book at hand presents a careful selection of relevant applications of CI methods for transport, logistics, and supply chain management problems. The chapters illustrate the current state-of-the-art in the application of CI methods in these fields and should help and inspire researchers and practitioners to apply and develop efficient methods. A few contributions in this book are extended versions of papers presented at EvoTransLog2007: The First European Workshop on Evolutionary Computation in Transportation and Logistics which was held in Valencia, Spain, in 2007. The majority of contributions are from additional, specially selected researchers, who have done relevant work in different areas of transport, logistics, and supply chain management. The goal is to broadly cover representative applications in these fields as well as different types of solution approaches. On the application side, the contributions focus on design of traffic and transportation networks, vehicle routing, and other important aspects of supply chain management such as inventory management, lot sizing, and lot scheduling. On the method side, the contributions deal with evolutionary algorithms, local search approaches, and scatter search combined with other CI techniques such as neural networks or fuzzy approaches. The book is structured according to the application domains. Thus, it has three parts dealing with traffic and transportation networks, vehicle routing, and supply chain management.

Engineering. --- Software engineering. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Automotive engineering. --- Engineering economics. --- Engineering economy. --- Automotive Engineering. --- Artificial Intelligence (incl. Robotics). --- Appl.Mathematics/Computational Methods of Engineering. --- Software Engineering. --- Engineering Economics, Organization, Logistics, Marketing. --- Economy, Engineering --- Engineering economics --- Industrial 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 --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer software engineering --- Construction --- Industrial arts --- Technology --- Mathematics --- Business logistics. --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Supply chain management --- Industrial management --- Logistics --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- Transportation. --- Public transportation --- Transport --- Transportation --- Transportation, Primitive --- Transportation companies --- Transportation industry --- Locomotion --- Commerce --- Communication and traffic --- Storage and moving trade --- Economic aspects

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Evolutionary computation (EC) techniques are e?cient nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and the simple underlying principles, these methods can be used for a large number of problems in the context of problem solving,optimization,andmachinelearning. Alargeandcontinuouslyincreasing number of researchers and practitioners make use of EC techniques in many - plication domains. The book at hand presents a careful selection of relevant EC applications combined with thorough examinations of techniques for a successful application of EC. The presented papers illustrate the current state of the art in the application of EC and should help and inspire researchers and practitioners to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoWorkshops 2005, which was a varying collection of workshops on application-oriented aspects of EC. Since 1999, the format of the EvoWorkshops has proved to be very successful and well representative of the advances in the application of EC. Consequently, over the last few years, EvoWorkshops has become one of the major events addressing the application of EC. In contrast to other large conferences in the EC ?eld, the EvoWorkshops focus solely on application aspects of EC and are an important link between EC research and the application of EC in a large variety of di?erent domains.

Computer science. --- Computer programming. --- Computers. --- Computer networks. --- Computer science—Mathematics. --- Computer vision. --- Theory of Computation. --- Programming Techniques. --- Computer Hardware. --- Computer Communication Networks. --- Mathematical Applications in Computer Science. --- Computer Vision. --- Evolutionary programming (Computer science) --- Evolutionary computation