Hybrid Metaheuristics  [electronic resource] / 
edited by El-Ghazali Talbi. 
 - XXVI, 458 p.  online resource. 
 - Studies in Computational Intelligence,  434  1860-949X ; .
 - Studies in Computational Intelligence,  434 .
<br/><br/>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. 
<br/><br/> 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. 
<br/><br/><label>ISBN: </label>9783642306716 
<br/><br/><label>Standard No.: </label>10.1007/978-3-642-30671-6  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Engineering.<br/>Artificial intelligence.<br/>Computational intelligence.<br/>Engineering.<br/>Computational Intelligence.<br/>Artificial Intelligence (incl. Robotics).
<br/><br/><label>LC Class. No.: </label>Q342 
<br/><br/><label>Dewey Class. No.: </label>006.3