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The algorithm adopts the ABC algorithm that emphasizes the global search capability, which is based on iterative feedback information. It uses single-element points, multi-element points, and iteration constraints to optimize the strategies of employed bees, follower bees, and scout bees, respectively. In terms of time and priority, simulation experiments prove that the IB-ABC algorithm can balance local and global search capabilities, accelerate the speed of convergence, and realize multi-UAV path planning in complex mountain environments.<\/jats:p>","DOI":"10.1017\/s0263574722001680","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T14:12:28Z","timestamp":1670854348000},"page":"1244-1257","source":"Crossref","is-referenced-by-count":12,"title":["Multi-UAV path planning based on IB-ABC with restricted planned arrival sequence"],"prefix":"10.1017","volume":"41","author":[{"given":"Li","family":"Tan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8096-1474","authenticated-orcid":false,"given":"Jiaqi","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Haoyu","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Hongtao","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2022,12,12]]},"reference":[{"key":"S0263574722001680_ref12","unstructured":"[12] R. 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