Tabu Search with variable partitioning for high dimensional problems

Meta-heuristics have been successfully applied to solve different types of problems. However, the contributions of meta-heuristics that deal with high dimensional problems are still very limited compared with low and middle dimensional problems. Tabu Search (TS) represents popular class of meta-heuristics. In this paper, a short term TS algorithm based on variable partitioning is proposed for solving high dimensional problems. Numerical results show that the proposed method is promising and produces high quality solutions with low computational costs.