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About

Yassine Meraihi is a leading researcher in the field of metaheuristic optimization, with a particular focus on nature-inspired algorithms and their applications to complex real-world problems. His major contributions include comprehensive surveys and novel hybridizations of swarm intelligence algorithms, most notably the Dragonfly Algorithm, Sine Cosine Algorithm, and Manta Ray Foraging Optimization. His 2020 review of the Dragonfly Algorithm has garnered 200 citations, establishing it as a foundational reference in the field, while his 2021 survey of the Sine Cosine Algorithm has accumulated 178 citations, demonstrating the high impact of his synthesis work. In a notable applied contribution, Meraihi developed a Hybrid Improved Manta Ray Foraging Optimization with Tabu Search to solve the UAV placement problem in smart cities (2023, 22 citations), showcasing his ability to bridge theoretical optimization with pressing urban technological challenges. His most recent comprehensive survey on Manta Ray Foraging Optimization (2025) further cements his role as a leading synthesizer and innovator in metaheuristic research. Meraihi’s work is essential reading for researchers and students exploring advanced optimization techniques for engineering, IoT, and smart city applications.