Design of Modern Heuristics: Principles and Application

Description

Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems. This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use. Front Matter....Pages I-XI Introduction....Pages 1-4 Front Matter....Pages 5-5 Optimization Problems....Pages 7-44 Optimization Methods....Pages 45-102 Front Matter....Pages 103-103 Design Elements....Pages 105-129 Search Strategies....Pages 131-155 Design Principles....Pages 157-171 Front Matter....Pages 173-173 High Locality Representations for Automated Programming....Pages 175-183 Biased Modern Heuristics for the OCST Problem....Pages 185-220 Summary....Pages 221-225 Back Matter....Pages 227-267