An application of Imperialist Competitive Algorithm to solve the quadratic assignment problem

Imperialist Competitive Algorithm (ICA) is a new socio-politically motivated global search strategy that has recently been introduced for dealing with different optimization problems. In this paper, we adopt ICA to solve the quadratic assignment problem which is a NP-Complete problem and is one of the most interesting and most challenging combinatorial optimization problems in existence. We test our algorithm on some of the benchmark instances of QAPLIB, a well-known library of QAP instances. This algorithm is compared with two meta heuristic strategies. These methods are based on simulated annealing approach and genetic algorithm. In most of instances, the proposed method outperforms other approaches. Experimental results illustrate the effectiveness of ICA approach on the quadratic assignment problem.