Solving Competitive Facilities Location Problem with the Clonal Selection Algorithm

Competitive facility location (CFL) problem has been proved to be NP-hard. Most location-allocation solution methods rely on heuristic approaches, however, they do not guarantee a global optimal solution. This paper proposes an improved clonal selection algorithm, which is an important theory in artificial immune systems (AIS), and we apply it to the CFL task. A special string is used as the shape-space in immune cell pattern. In addition, we propose an n-hold method to improve the performance of AIS, which can increase the stability and robustness of the clonal selection algorithm. Meanwhile, a special version of the roulette wheel method is proposed to improve the algorithm performance. And we give the evolutionary explain of AIS. Experiments show that the proposed algorithm is effective and efficient to the CFL task