A Hybridization of Ant Colony Optimization and Tabu Search Meta-heuristics for Continuous Problems

A new hybrid optimization method, combining Continuous Ant Colony System (CACS) and Tabu Search (TS) is proposed for minimization of continuous multi – minima functions. The new algorithm incorporates the concepts of promising list, tabu list and tabu balls from TS into the framework of CACS. This enables the resultant algorithm to avoid bad regions and to be guided toward the areas more likely to contain the global minimum. A new strategy is proposed to dynamically tune the radius of the tabu balls during the execution of the algorithm. The promising list is also used to update the pheromone distribution over the search space. The parameters of the new method are tuned based on the results obtained for a set of standard test functions. The results of the proposed scheme are also compared with those of some other meta-heuristics. The comparisons show an improvement in terms of accuracy and efficiency.

کلیدواژه ها:

Ant Colony Optimization ، Tabu Search ، Hybrid Meta-heuristics ، Global Optimization ، Continuous Optimization