A hybrid nested partitions optimization algorithm for the QAP problem

This paper proposes a hybrid optimization algorithm based on nested partitions method (NPM) framework for solving quadratic assignment problem (QAP). In the algorithm, the QAP is described as a nested partitions tree. The algorithm systematically partitions the feasible region and uses tabu search sampling operator to evaluate the performance of each subregion. In the each iteration, the algorithm focused on the most promising region for searching the optimal solutions. And the tabu search is incorporated into the sampling procedure to make the subregion correct move. The results of numerical experiments show that the hybrid algorithm has better performance.