Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques
Springer Science & Business Media, Mar 20, 2006 - Computers - 626 pages
Search Methodologies is a tutorial survey of the methodologies that are at the confluence of several fields: Computer Science, Mathematics and Operations Research. It is a carefully structured and integrated treatment of the major technologies in optimization and search methodology. The book is made up of 19 chapters. The chapter authors are drawn from across Computer Science and Operations Research and include some of the world’s leading authorities in their field. The result is a major state-of-the-art tutorial text of the main optimization and search methodologies available to researchers, students and practitioners across discipline domains in applied science. It can be used as a textbook or a reference book to learn and apply these methodologies to a wide range of today’s problems. It has been written by some of the world’s most well known authors in the field.
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antibodies applications approximation algorithms artificial immune systems attributes behavior binary branch and bound Chapter color complexity Computer Science Conf constraint programming criteria crossover decision rules defined denoted dominance Dorigo evaluation evolutionary algorithms Evolutionary Computation example Figure flow formulation Free Lunch fuzzy control fuzzy logic Fuzzy Sets genetic algorithms genetic programming given global Goldberg graph heuristic hyper-heuristic IEEE implementation input integer programming iteration Koza landscape learning algorithms machine learning metaheuristics minimal multi-objective optimization mutation neural networks node non-dominated objective function operator optimal solution optimization problems optimum output parameters Pareto-optimal particle performance permutation pheromone pheromone values polynomial population possible prob Proc random Rough Set Rough Set Approach scheduling search algorithms search space selection simulated annealing Slowinski solve Springer step strategy subset swarm tabu search task techniques theory tion tree update variables vector