Distributed Multistart Hybrid Iterative Tabu Search

The quadratic assignment problem (QAP) is one of the most studied NP-hard problems. It is a problem known for its computational cost which makes it a good candidate for parallel and distributed design. In this paper, we propose a new Distributed Multistart Hybrid Iterative Tabu Search (DMHITS). This algorithm follows the design of the algorithmic level. Through 34 of the hardest well-known instances from QAPLIB benchmark, the DM-HITS can get the best known solution for almost all the instances. From the 340 runs on these benchmark instances, our algorithm gets more than 300 times the best known solution. This experimentation shows that our proposed algorithm can exceed or equal six leading algorithms from the literature.