Tournament Selection based Antlion Optimization Algorithm for Solving Quadratic Assignment Problem
AbstractQuadratic Assignment Problem (QAP) is based the facilities allocation, and it is a difficult combinatorial optimization problem. The objective of this problem is to make total assignment cost minimum while being assigned facilities to locations that are already known. To solve this problem, the different methods are used in the literature. Meta-heuristic algorithms are ones from these methods and in this study, we present a new version of recent antlion optimization algorithm for QAP. AntLion Optimization (ALO) algorithm was developed by Mirjalili in 2015. ALO algorithm is based on the hunting behaviour of the antlion. This algorithm comprises five stages: random walking mechanism, constructing trap, trapping in the antlion’s pit, sliding ants in the pit, catching the prey and reconstructing the pit. Although ALO algorithm is successful in benchmark functions of multi dimensions, it has got some drawbacks. The most notable improvement is the use of tournament method instead of roulette wheel method. In ALO algorithm, the antlion is chosen from the population by roulette wheel method for using in each ant's random walking model. The roulette wheel method is more successful in maximization problems. In the minimization problems, the tournament selection method is more efficient method than the other selection methods Therefore, we used the tournament selection method in this study instead of the roulette wheel method on random walking mechanism. This proposed algorithm has been called the tournament selection based antlion optimization algorithm (TALO). To evaluate the performance of TALO algorithm, we used well-known meta-heuristic algorithms. The results provide the proposed TALO algorithm has the best performance in comparison with those of the other algorithms.