Foraging-Inspired Optimisation Algorithms - Anthony Brabazon,Seán Mcgarraghy
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This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organism ... Full description
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Description
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains.
More Information
| Author | Anthony Brabazon, Seán Mcgarraghy |
|---|---|
| Publisher | Springer Nature Switzerland |
| Series | Natural Computing Series |
| Release year | 2019 |
| Cover type | Softcover |
| EAN | 9783030096403 |