Advanced Optimization Algorithm: VROA - Tapa blanda

Sinopsis

Nature Inspired methods play a most important and highly effective role in handling the large-scale optimization applications which furthermore have been stimulated via co-operative intelligence of creatures in wildlife or nature. This study presents a novel population based approach enthused via ‘Velociraptor’ social intelligence in wildlife (or nature), known as Velociraptor Groups Optimization algorithm (VROA). In this strategy, ‘Velociraptor’ co-operative natural life cycle is mathematically framed, and novel mechanisms are presented to perform search (or exploration)and hunting (or exploitation). In the direction of assessing the VROA, we utilized it to 51 CEC’17, CEC’20 and CEC’22 standard benchmark suites and six multi-disciplinary engineering optimization functions. Further, well-known statistical methods like Wilcoxon rank-sum test and Friedman’s test have been utilized for verifying the strength of the proposed algorithm with various optimizers. Tabulated numerical and statistical solutions show that the VROA performs superior than recent optimizers on most standard test suites. The outcomes validate that the VROA can offer efficient and accurate optima solutions as evaluation with recent metaheuristics.

This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field.

This book is certainly a small sample of the research activity on Velociraptor Groups Optimization algorithm (VROA) going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects.

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