Bioheuristics as Tool for Global Optimization Problem Based on Collective Behavior Model of Animals

The main purpose of the article is to develop an effective algorithm for solving applied problems of global optimization of multidimensional unimodal and multimodal functions. Such functions are encountered in issues of engineering design, image processing and computer vision, energy and energy management, data analysis and machine learning, robotics. To achieve this goal, the article proposes a computational model of the collective behavior of a group of animals and an effective algorithm for differential vector movement. The algorithm was experimentally tested on known multidimensional unimodal and multimodal functions. The results were compared with competing algorithms. The obtained results using Wilcoxon rank-sum test for independent samples showed that the results of the algorithm are statistically significant.