الصفحة 1
الصفحة 1
Multiobjective Optimization : Interactive and Evolutionary Approaches
Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support.
Applications of evolutionary computing ; Vol. 3907 : EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Budapest, Hungary, April 10-12, 2006, Proceedings
This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2006, held in Budapest, Hungary, in April 2006. The 65 revised full papers and 13 revised short papers presented were carefully reviewed and selected from a total of 149 submissions. In accordance with the seven workshops covered, the papers are organized in topical sections on evolutionary bioinformatics, evolutionary computation in communications, networks, and connected systems, evolutionary computation in hardware optimization, evolutionary computation in image analysis and signal processing, interactive evolution and humanized computational intelligence, evolutionary music and art, and evolutionary algorithms in stochastic and dynamic environments.
Applications of evolutionary computing ; Vol. 3449 ; Evoworkshops : EvoBIO, EvoCOMNET, EvoHot, EvoIASP, EvoMUSART, and EvoSTOC
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.
