Neighborhood Clonal Selection Learning Algorithm and its application

In this paper, we propose a Neighbourhood Clonal Selection Learning Algorithm(N-Clonalg), which is combined with the idea of artificial immune system and Agent technology. Based on the grid environment, the individuals in N-Clonalg do local and global searching operators. Unlike other artificial immune algorithms, N-Clonalg has three main search operators, i.e. Neighbourhood Clonal Selection, Neighbourhood Competition and Self-learning. Combining the global and local search, N-Clonalg overcomes the phenonmena of premature and slow convergence, and can effectively get the global optimals. Distillation resources optimization shows that it has better search performance.