Abstract

The Quadratic Assignment problem (QAP) is one of the most studied optimization problem. Although many direct and heuristic methods are used to give the solution of QAP for small size instances in reasonable time but it takes huge time for large size instances. So, solving QAP in massively parallel architecture like Graphics processing unit (GPU) by applying a noble metaheuristics Crow Search Algorithm (CSA) can further optimize the solution and their execution time. So, in this paper we analyse the QAP in accelerated systems by using CSA metaheuristics and CSA performs approximately 10 times faster on GPU as compared to CPU.

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