关键词: 蚁群优化算法, 信息交流策略, 全局搜索

Abstract: When the continuous domain ant colony optimization algorithm（ACOR） solves the optimization problem, the global optimization ability is weak, and the accuracy of the optimization result is low. Inspired by the mutual exchange and combination between the excellent individuals in nature can produce better offspring, a continuous domain ant colony optimization algorithm（ICACO） based on information exchange strategy is proposed. The ICACO algorithm selects some of the better solutions in the process of updating the solution and uses the information exchange strategy to process the candidate solutions, and adopts a greedy method to accept candidate solutions that can improve the solution quality. The proposed algorithm is tested by the standard test function. The experimental results show that the ICACO algorithm can effectively improve the accuracy of the ACOR algorithm and speed up the convergence. This algorithm has better global search ability and better performance than related improved continuous domain ant colony algorithm and other intelligent optimization algorithms.

Key words: ant colony optimization algorithm, information exchange strategy, global search