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Harmony Search Algorithm : Proceedings of the 3rd International Conference on Harmony Search Algorithm
About this item
This volume presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date in the literature: Harmony Search. Contributions will span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation & mobility and health, among many others. Novel contributions are expected not only on its cross-domain applicability, but also on its core evolutionary operators, including elements inspired from other meta-heuristics.
The worldwide scientific community is witnessing an upsurge of new path-breaking advances in all areas of computational intelligence, with a particularly notable flurry of research focused on evolutionary computation and bio-inspired optimization. Observed processes in nature and sociology have laid the basis for innovative algorithmic developments aimed at leveraging the inherent capability to adaptation featured by ants, fireflies, wolves, humans and other animals. However, it is the behavioral patterns observed in music composition which motivated the advent of the Harmony Search algorithm, a meta-heuristic optimization algorithm that has been shown during the last decade to dominate other solvers in a plethora of application scenarios.
The audience is expected to be the research community working on different applications and deriving novel approaches around meta-heuristic optimization, with an emphasis on Harmony Search. ICHSA is the biggest biannual event where world-wide experts on meta-heuristic optimization present their latest findings, and where the most renowned individuals in the field of Harmony Search optimization meet and discuss the past, present and future of this exciting field.
This book is composed by a selection of the best-quality contributions presented in this forum, and embodies a reference material for early-bird researchers working in the field of optimization meta-heuristics, and a solid technical base for frontline investigations around this algorithm.