Clonal Selection Algorithm with Adaptive Mutation and Roulette Wheel Selection

In this paper, roulette wheel selection strategy and adaptive mutation operation were introduced to the basic immune clonal selection algorithm (ICSA) in order to overcome premature convergence and stagnation at the end stage of iterative optimization. The method was utilized to optimize two types of typical testing functions and the simulation results show that the algorithm can improve the ability of searching the global optimum and yield superior results compared with the basic immune clonal selection algorithm.