In this paper a candidate list strategy for neighborhood based iterative search methods in the area of circuit based problems is developed. In problems like different versions of TSP and VRP, when the neighboring solutions of the current solution are too many to be explored, neighborhood based search methods do not work well. Candidate list strategy is a wise way to select a small percentage of the neighboring solutions to be passed to the search algorithm. Based on a logical rule, the strategy eliminates most of the neighborhood solutions which are probably of no good quality. In this paper a candidate list strategy for circuit based problems, especially large TSP’s, is presented and tested to be contained within Tabu search or any typical neighborhood based metaheuristic. The strategy is dynamic and makes use of the fact that large edges are not likely to be in the optimal tour. In fact, our method is an extension to the well known granular Tabu search- GTS- method originally developed for the VRP. Experiments show that the strategy makes the search faster while it does not have a significant effect on the quality of the best solution found.
