Modified Artificial Gorilla Troop Optimization Algorithm for Solving Constrained Engineering Optimization Problems

The artificial Gorilla Troop Optimization (GTO) algorithm is a metaheuristic optimization that simulates the social life of gorillas. This paper proposes three innovative strategies considering GTO algorithm’s insufficient convergence accuracy and low speed. First, shrinkage control factor fusion strategy proposed to expand search space reduce blindness by strengthening communication between silverback gorillas other improve global performance. Second, sine cosine interaction based on closeness stabilize performance gorilla individuals ability speed algorithm. Finally, individual difference identification quality optimal solution. In order verify effect modified troop (MGTO) algorithm, we used 23 classic benchmark functions, 30 CEC2014 10 CEC2020 functions test MGTO this study, total 63 for comparison. At same time, carried out exploitation exploration balance experiment addition, was also applied seven practical engineering problems, it achieved good results.