Optimization techniques for solving complex problems / 
edited by Enrique Alba, Christian Blum, Pedro Isasi  [and 2 others]. 
 - Hoboken, New Jersey :  Wiley,  c2009 
 - xxi, 476 pages :  illustrations ;  24 cm. 
<br/><br/>Includes bibliographical references and index. 
<br/><br/>OPTIMIZATION TECHNIQUES FOR SOLVING COMPLEX PROBLEMS; CONTENTS; CONTRIBUTORS; FOREWORD; PREFACE; PART I METHODOLOGIES FOR COMPLEX PROBLEM SOLVING; 1 Generating Automatic Projections by Means of Genetic Programming; 2 Neural Lazy Local Learning; 3 Optimization Using Genetic Algorithms with Micropopulations; 4 Analyzing Parallel Cellular Genetic Algorithms; 5 Evaluating New Advanced Multiobjective Metaheuristics; 6 Canonical Metaheuristics for Dynamic Optimization Problems; 7 Solving Constrained Optimization Problems with Hybrid Evolutionary Algorithms. 
<br/><br/> Solving Complex Problems addresses real problems and the modern optimization techniques used to solve them. Thorough examples illustrate the applications themselves, as well as the actual performance of the algorithms. Application areas include computer science, engineering, transportation, telecommunications, and bioinformatics, making the book especially useful to practitioners in those areas. 
<br/><br/><label>ISBN: </label>9780470293324 
<br/><br/><label>Subjects--Topical Terms: </label><br/>COMPUTER SCIENCE -- MATHEMATICS
<br/><br/><label>LC Class. No.: </label>QA 76.9 .O68 2009