Investigation of a changing range genetic algorithm in noisy environments

This paper analyses the effect of noise on the performance of a changing range genetic algorithm (CRGA). CRGA adaptively shifts and shrinks the size of the search space of the feasible region by employing feasible and infeasible solutions in the population to reach the global optimum. An additional modification of CRGA was introduced to reduce the effects of noise on the performance of the algorithm. Several test cases demonstrated the ability of the improved CRGA to deal with an additive noise. Copyright q 2007 John Wiley & Sons, Ltd