Dogfight Search: A Swarm-Based Optimization Algorithm for Complex Engineering Optimization and Mountainous Terrain Path Planning

2026-03-30

AI Summary

This study addresses the challenge of global optimization in complex engineering design and mountainous path planning by proposing a metaphor-free swarm intelligence algorithm. Departing from conventional bio-inspired metaphors, the method derives its search framework directly from fighter jet cooperative dogfighting tactics and constructs a physically meaningful search mechanism grounded in kinematic displacement integral equations, effectively balancing exploration and exploitation. Integrated with an efficient constraint-handling strategy, the algorithm is well-suited for high-dimensional, nonlinear, and highly constrained problems. Comprehensive evaluations on CEC2017/2022 benchmark suites, ten real-world engineering optimization problems, and mountain path planning tasks demonstrate its superior performance over seven state-of-the-art algorithms and three recent top-performing methods, achieving the best average rank in Friedman tests.

Abstract

Dogfight is a tactical behavior of cooperation between fighters. Inspired by this, this paper proposes a novel metaphor-free metaheuristic algorithm called Dogfight Search (DoS). Unlike traditional algorithms, DoS draws algorithmic framework from the inspiration, but its search mechanism is constructed based on the displacement integration equations in kinematics. Through experimental validation on CEC2017 and CEC2022 benchmark test functions, 10 real-world constrained optimization problems and mountainous terrain path planning tasks, DoS significantly outperforms 7 advanced competitors in overall performance and ranks first in the Friedman ranking. Furthermore, this paper compares the performance of DoS with 3 SOTA algorithms on the CEC2017 and CEC2022 benchmark test functions. The results show that DoS continues to maintain its lead, demonstrating strong competitiveness. The source code of DoS is available at https://ww2.mathworks.cn/matlabcentral/fileexchange/183519-dogfight-search.

Problem

• engineering optimization
• path planning
• mountainous terrain
• constrained optimization
• metaheuristic algorithm

Innovation

• metaphor-free optimization
• kinematic displacement integration
• swarm intelligence
• constrained engineering optimization
• mountainous terrain path planning