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Iterative Optimizers: Difficulty Measures and Benchmarks (Computer Engineering) - Hardcover

 
9781786304094: Iterative Optimizers: Difficulty Measures and Benchmarks (Computer Engineering)

Synopsis

Almost every month, a new optimization algorithm is proposed, often accompanied by the claim that it is superior to all those that came before it. However, this claim is generally based on the algorithm's performance on a specific set of test cases, which are not necessarily representative of the types of problems the algorithm will face in real life.

This book presents the theoretical analysis and practical methods (along with source codes) necessary to estimate the difficulty of problems in a test set, as well as to build bespoke test sets consisting of problems with varied difficulties.

The book formally establishes a typology of optimization problems, from which a reliable test set can be deduced. At the same time, it highlights how classic test sets are skewed in favor of different classes of problems, and how, as a result, optimizers that have performed well on test problems may perform poorly in real life scenarios.

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About the Author

Maurice Clerc is recognized as one of the foremost particle swarm optimization specialists in the world. A former France Telecom Research and Development engineer, he maintains his research activities as a consultant for optimization projects.

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  • PublisherWiley-ISTE
  • Publication date2019
  • ISBN 10 1786304090
  • ISBN 13 9781786304094
  • BindingHardcover
  • LanguageEnglish
  • Edition number1
  • Number of pages224

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Hardcover. Condition: new. Hardcover. Almost every month, a new optimization algorithm is proposed, often accompanied by the claim that it is superior to all those that came before it. However, this claim is generally based on the algorithm's performance on a specific set of test cases, which are not necessarily representative of the types of problems the algorithm will face in real life. This book presents the theoretical analysis and practical methods (along with source codes) necessary to estimate the difficulty of problems in a test set, as well as to build bespoke test sets consisting of problems with varied difficulties. The book formally establishes a typology of optimization problems, from which a reliable test set can be deduced. At the same time, it highlights how classic test sets are skewed in favor of different classes of problems, and how, as a result, optimizers that have performed well on test problems may perform poorly in real life scenarios. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781786304094

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