Abstract: In this paper, a crow search algorithm which is a type of swarm intelligence optimization algorithm proposed by simulating the crows' intelligent behavior of hiding and retrieving food.
It is used to solve the Quadratic Assignment Problem (QAP) which is a NP-Complete problem.
It is assumed one of the complex combinatorial optimization problems related with assigning a set of facilities to a set of locations in condition of minimizing the total assignment cost.
The used technique is modified to be allowed to apply on the desired problem.
It is used the Smallest Position Value (SPV) heuristic rule to transform the generated continuous solution from crow search algorithm to a discrete one to be suitable to this kind of problems.
Based on ten benchmark problems with different sizes, the computational results show that the used algorithm is capable to find the optimal and best-known solutions. Thus, the proposed method exceeds other illustrated methods. Experimental results show its effectiveness on the quadratic assignment problems