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This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate studentsin the area of swarm intelligence and computational intelligence and working on these topics.
List of contents
Preface.- Acknowledgements.- 1 From Natural to Synthetic Swarms.- 2 Glowworm Swarm Optimization: Algorithm Development.- 3 Theoretical Foundations.- 4 Multimodal Function Optimization.- 5 Experiments using Physical Simulations and Real Robots.- 6 Applications to Ubiquitous Computing Environments.- 7 Pursuit of Multiple Mobile Signal Sources.- 8 GSO Applications and Extensions.
Summary
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate studentsin the area of swarm intelligence and computational intelligence and working on these topics.
