Gary B. Lamont – författare
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5 produkter
Evolutionary Algorithms for Solving Multi-Objective Problems
Av Carlos Coello Coello, Gary B. Lamont m. fl.
Inbunden, 2007
1466 kr
Lägg i varukorg
Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic …
Evolutionary Algorithms for Solving Multi-Objective Problems
Av David A. van Veldhuizen, Gary B. Lamont m. fl.
E-bok, 2007
1260 kr
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Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic …
Evolutionary Algorithms for Solving Multi-Objective Problems
Av Gary B. Lamont, David A. Van Veldhuizen m. fl.
E-bok, 2013
1174 kr
Lägg i varukorg
Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are …
Evolutionary Algorithms for Solving Multi-Objective Problems
Av Carlos Coello Coello, Gary B. Lamont m. fl.
Häftad, 2014
989 kr
Lägg i varukorg
Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic …
APPLICATIONS OF MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
Av Carlos A Coello Coello, Gary B Lamont m. fl.
Inbunden, 2004
4449 kr
Tillfälligt slut
This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good …