An ejection chain algorithm for the quadratic assignment problem

In this study, we present a new tabu search algorithm for the quadratic assignment problem (QAP) that utilizes an embedded neighborhood construction called an ejection chain. Our ejection chain approach provides a combinatorial leverage effect, where the size of the neighborhood grows multiplicatively while the effort of finding a best move in the neighborhood grows only additively. Our results illustrate that significant improvement in solution quality is obtained in comparison to the traditional swap neighborhood. We also develop two multistart tabu search algorithms utilizing the ejection chain approach in order to demonstrate the power of embedding this neighborhood construction within a more sophisticated heuristic framework. Comparisons to the best large neighborhood approaches from the literature are presented