Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implem...
An introduction to genetic algorithms, pp. 117{117. MIT press 25. Goldberg, D.E.: optimization and machine learningMitchell, M
An Introduction to Genetic Algorithms. MIT Press, Cambridge While Pareto-based multi-objective optimization algorithms continue to show effectiveness for a wide range of practical problems that involve mostly two or... M Mitchell - DBLP 被引量: 1773发表: 1998年 An Introduction to Genetic Algorithms...
Genetic algorithms have been applied in a vast number of ways. This discussion is limited to the optimization of a numerical function. Following the convention of computer programs, the problem will be considered to be a minimization. (If you want to maximize, then minimizing the negative of yo...
An Introduction to Genetic Algorithms (MIT Press, 1996). Baumert, T., Brixner, T., Seyfried, V., Strehle, M. & Gerber, G. Femtosecond pulse shaping by an evolutionary algorithm with feedback. Applied Physics B: Lasers and Optics 65, 779–782 (1997). Article ADS CAS Google Scholar ...
An optimization perspective on global search methods is featured and includes discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. In addition, the book includes an elementary introduction to artificial neural networks, convex optimization, and multi-objective...
Finally, nonlinear programming methods are designed to solve optimization problems some of the constraints or objective functions are nonlinear. For a more detailed introduction to optimization methods and techniques, see Ref. [12]. A range of software tools are available for solving optimization ...
《AnIntroductiontoOptimization(WileySeriesinDiscreteMathematicsandOptimization)》作者:Wiley-Interscience,出版社:2008年2月,ISBN:895.70。PraisefromtheSecondEdition
An Introduction to Kernel Methods: 10.4018/978-1-60566-010-3.ch170: Machine learning has experienced a great advance in the eighties and nineties due to the active research in artificial neural networks and adaptive systems.
Jasbir S.Arora, inIntroduction to Optimum Design (Second Edition), 2004 17.3Multiobjective Genetic Algorithms Geneticalgorithms (GAs) for single-objective optimization can be extended to provide an effective approach for solving multiobjectiveoptimization problemsas well. Since GAs for multiobjective optim...