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Traditional methods show limitations in dealing with these complex nonlinear models. To address these challenges, the swarm intelligence algorithm is introduced as a metaheuristic method and effectively implemented. However, existing technology exhibits drawbacks such as slow convergence speed, low precision, and poor robustness. In this paper, we propose a novel metaheuristic approach called the Red-billed Blue Magpie Optimizer (RBMO), inspired by the cooperative and efficient predation behaviors of red-billed blue magpies. The mathematical model of RBMO was established by simulating the searching, chasing, attacking prey, and food storage behaviors of the red-billed blue magpie. To demonstrate RBMO\u2019s performance, we first conduct qualitative analyses through convergence behavior experiments. Next, RBMO\u2019s numerical optimization capabilities are substantiated using CEC2014 (Dim\u2009=\u200910, 30, 50, and 100) and CEC2017 (Dim\u2009=\u200910, 30, 50, and 100) suites, consistently achieving the best Friedman mean rank. In UAV path planning applications (two-dimensional and three\u2009\u2212\u2009dimensional), RBMO obtains preferable solutions, demonstrating its effectiveness in solving NP-hard problems. Additionally, in five engineering design problems, RBMO consistently yields the minimum cost, showcasing its advantage in practical problem-solving. We compare our experimental results with three categories of widely recognized algorithms: (1) advanced variants, (2) recently proposed algorithms, and (3) high-performance optimizers, including CEC winners.<\/jats:p>","DOI":"10.1007\/s10462-024-10716-3","type":"journal-article","created":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T04:02:16Z","timestamp":1714708936000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":311,"title":["Red-billed blue magpie optimizer: a novel metaheuristic algorithm for 2D\/3D UAV path planning and engineering design problems"],"prefix":"10.1007","volume":"57","author":[{"given":"Shengwei","family":"Fu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haisong","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chi","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingsong","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunwei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,3]]},"reference":[{"key":"10716_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.110248","author":"M Abdel-Basset","year":"2023","unstructured":"Abdel-Basset M, Mohamed R, Abouhawwash M (2023) Nutcracker optimizer: a novel naturE\u2009\u2212\u2009inspired metaheuristic algorithm for global optimization and engineering design problems. 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