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2 claims from 1 paper

1. Computer Science › Metaheuristic Optimization Algorithms Research

   Multi-strategy improved gazelle optimization algorithm for numerical optimization and UAV path planning

   Li, Zhao, Lyu and Yang · Scientific Reports · 2025

   The authors improve the Gazelle Optimization Algorithm with several strategies, call it MIGOA, and test it on benchmark sets, UAV path planning and two engineering design problems.

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   1. UncheckedOn CEC2017 and CEC2020 benchmarks, MIGOA has average rankings of 1.80, 2.03, 2.03 and 2.70, ahead of standard GOA and other optimizers.“The results, validated by the Wilcoxon rank-sum test and the Friedman mean rank test, demonstrate that MIGOA achieves average rankings of 1.80, 2.03, 2.03, and 2.70 on CEC2017 (Dim = 30/50/100) and CEC2020 (Dim = 20), respectively, outperforming the standard GOA and other high-performance optimizer…”
   2. UncheckedApplying MIGOA to 3D UAV path planning and two engineering design problems is said to further show its potential for constrained optimisation.“Furthermore, the application of MIGOA to three-dimensional unmanned aerial vehicle (UAV) path planning problems and 2 engineering optimization design problems further validates its potential in solving constrained optimization problems.”