Gazelle Optimization Algorithm with Multi-strategy and Its Application

Gazelle Optimization Algorithm (GOA) is a heuristic optimization algorithm based on gazelle behavior in nature. Inspiration comes from the gazelle's ability to survive in predator-dominated environments, and the gazelle's ability to maintain high speed and flexibility when running across the savannah inspired the design of the gazelle optimization algorithm. However, due to its shortcomings of falling into local minima and slow convergence, a Gazelle optimization algorithm with Multi-strategy(TLGOA) is proposed. In the initial stage, tent chaotic map is added to initialize the population, and then the refraction reverse learning strategy is used to improve the diversity and quality of the population, which can effectively improve the convergence speed of the algorithm. Finally, the optimization method of golden section number optimization GOA is introduced to coordinate the global exploration and local development ability of the algorithm. Through testing and comparative analysis of various international benchmark functions, the results show that TLGOA has obvious convergence speed and conversion accuracy. Finally, TLGOA is used to solve the Traveling salesman problem (TSP), and the results are remarkable.