Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
In dynamic environments or multiobjective optimization problems, it is important to acquire two or more quasi-optimal solutions. However, the conventional single colony model in ant colony optimization (ACO) cannot keep diverse good solutions due to convergence of ants' behavior. In order to solve the problem, we introduce tabu search mechanism into ACO. In this method, ants register the discovered solutions in a tabu list as ants search for the optimal solution. If the search converged, ants search different solutions from the solutions in the tabu list. We applied the proposed methods to traveling salesman problems. Some experimental results show that diverse solutions are acquired.
