New ideas in optimization
Author(s)
Bibliographic Information
New ideas in optimization
（Advanced topics in computer science series）
McGraw-Hill, c1999
- : pbk
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Note
Includes bibliographical references (p. [451]-481) and index
Description and Table of Contents
Description
Optimization is a pivotal aspect of software design. The techniques treated in this book represent the leading edge of research as elucidated by the leading researchers, many of whom are the originators of the methods. The volume editors are experienced and respected researchers and the subject is one of growing interest in advanced undergraduate and postgraduate programmes.There are a collection of well-known modern optimization methods being researched and applied to real problems worldwide. These include a variety of local search methods (hillclimbing, simulated annealing, tabu search, ...) and so-called evolutionary computation methods (genetic algorithms, genetic programming, evolutionary programming...). In recent years, a range of novel ideas have emerged in this research community, proposing new algorithms which are interestingly different from the current well-studied crop. In particular, these new ideas include: Ant Colony based optimisation, Scatter Search, Differential Evolution, Immune System Methods, Optima Linking, and Parallel Distributed Genetic Programming.
Table of Contents
Section 1: Ant Colony Optimization.
Section 2: Differential Evolution.
Section 3: Scatter Search and Path Relinking.
Section 4: Immune System Methods.
Section 5: Memetic Algorithms.
Section 6: Emerging Techniques and Extensions: Parallel Distributed Genetic Programming.
Co-evolutionary methods.
Guided Local Search.
Stepwise Adaptive Weight Algorithms.
Particle Swarm Methods.
by "Nielsen BookData"
