Library of American University of Madaba
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Talbi, El-Ghazali.
Hybrid Metaheuristics [electronic resource] / edited by El-Ghazali Talbi. - XXVI, 458 p. 109 illus. online resource. - Studies in Computational Intelligence, 434 1860-949X ; .
Part I Hybrid metaheuristics for mono and multi-objective optimization, and optimization under uncertainty -- Part II Combining metaheuristics with (complementary) metaheuristics -- Part III Combining metaheuristics with exact methods from mathematical programming approaches -- Part IV Combining metaheuristics with constraint programming approaches -- Part V Combining metaheuristics with machine learning and data mining techniques.
The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.
9783642306716
Engineering.
Artificial intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
006.3
Hybrid Metaheuristics [electronic resource] / edited by El-Ghazali Talbi. - XXVI, 458 p. 109 illus. online resource. - Studies in Computational Intelligence, 434 1860-949X ; .
Part I Hybrid metaheuristics for mono and multi-objective optimization, and optimization under uncertainty -- Part II Combining metaheuristics with (complementary) metaheuristics -- Part III Combining metaheuristics with exact methods from mathematical programming approaches -- Part IV Combining metaheuristics with constraint programming approaches -- Part V Combining metaheuristics with machine learning and data mining techniques.
The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.
9783642306716
Engineering.
Artificial intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
006.3