An effective dynamic weighted rule for ant colony system optimization

The ant colony system (ACS) algorithm is new metaheuristic for hard combinational optimization problems. It is a population-based approach that exploits positive feedback as well as greedy search. It was first proposed for tackling the well known traveling salesman problem (TSP). We introduce a new version of the ACS based on a dynamic weighted updating rule. Implementation to solve TSP and the performance results under various conditions are conducted, and the comparison between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with the original ACS in terms of solution quality and computation speed for these problem.