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This research paper aims to do a comparative study of three recent optimization metaheuristic approaches that had been applied to solve the NPhard optimization problem called the travelling salesman problem. The three recent metaheuristics in study are cuckoo search algorithm, cat swarm optimization algorithm and batinspired algorithm. To compare the performances of these methods, the three metaheuristics are applied to solve some benchmark instances of TSPLIB. The obtained results are collected and the error percentage is calculated. The discussion, will present which method is more efficient to solve the real application based on the travelling salesman problem.

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In recent years, there is a growing interest in swarm intelligent algorithms inspired by the observation of the natural behavior of swarm to define a computational method, which may resolve the hardest combinatorial optimization problems. The Quadratic Assignment Problem is one of the well-known combinatorial problems, which simulate with the assignment problem in several domains such as the industrial domain. This paper proposes an adaptation of a recent algorithm called the swallow swarm optimization to solve the Quadratic Assignment Problem; this algorithm is characterized by a hierarchy of search who allow it to search in a totality of research space. The obtained results in solving some benchmark instances from QAPLIB are compared with those obtained from other know metaheuristics in other to evaluate the performance of the proposed adaptation.