Beautiful Mind: a meta-heuristic algorithm for generating minimal covering array

Abstract

Abstract Today, the application of meta-heuristic algorithms in solving problems is very important. This importance has led to the development of hundreds of types of meta-heuristic algorithms by researchers. The reason for the high number of such algorithms is that an algorithm may be superior to its competitors in a particular problem. Generating a test set in Combinatorial Testing (CT) is one of the thousands of problems that can be solved by meta-heuristic algorithms and hundreds of algorithms have been proposed in this regard. The main challenge in producing a test set in CT is becoming trapped in local optima that several solutions have been offered to overcome this problem. Since the proposed solutions are very slow in terms of time, it is still possible to produce better results by applying other solutions. Continuing our research in the field of CT, we have tried to present a new meta-heuristic solution called Beautiful Mind (BM), which simulates the human way to reach the answer. In fact, the proposed algorithm considers the human intelligence and emotional coefficient to find the answer. The evaluation results show that the proposed approach is much stronger than the existing solutions.