An Chaotic Firefly Algorithm to Solve Quadratic Assignment Problem

The firefly algorithm (FA) is a swarm intelligence optimization algorithm based on the glow behavior of fireflies in nature. The classic firefly algorithm has the problem that it is easy to fall into the local optimum and the search accuracy is not high in the later stage. An improved firefly algorithm based on chaos mapping strategy was proposed to solve the quadratic assignment problem (QAP). The egocentricity of chaos just avoids the firefly algorithm from falling into the local optimum, enhances its search ability and solves the convergence prematurely phenomenon of the firefly algorithm. The improved algorithm is compared with genetic algorithm (GA), particle swarm optimization (PSO) algorithm and the classic firefly algorithm to solve the same quadratic assignment problems. The simulation experiments results verify the effectiveness of the proposed algorithm.