Exchange Strategies for Multi-Colony Ant Algorithms in Dynamic Environments - Mavrovouniotis, Michalis; Li, Changhe; Yazdani, Danial; Hadjimitsis, Diofantos G. (My University, 2024)
In dynamic optimization problems where optimal solutions change over time, traditional ant colony optimization (ACO) algorithms face limitations. This study explores the adaptation of multi-colony ACO algorithms, known for their enhanced search capabilities in stationary problems, to tackle optimization problems in dynamic environments. Various strategies for exchanging information between colonies, which is a critical factor influencing algorithm performance, are investigated. Using the dynamic traveling salesman problem as a foundation, we generate test cases to reflect real-world complexities. Our results on a set of problem instances reveal that the choice of communication strategy between colonies significantly impacts the adaptability and efficiency of multi-colony ACO algorithms in tracking moving optimum.
Keywords: Ant colony optimization; Multi-colony ant algorithm; Dynamic optimization problem; Dynamic traveling salesman problem; Tracking moving optimum