Application study on a novel differential evolution algorithm
Tan Shui-mu · Journal of Computer Applications · 2008
A novel algorithm based on simple diversity rules and Simple Improved Differential Evolution(SIDE)algorithm was proposed in this paper.It is characterized with the following new features:1)introducing a hybrid self-adaptive crossover-mutation operator,which can enhance the search ability and exploit the optimum offspring;2)using a new constraint-handling technique to maintain the diversity of the population;3)simplifying the scaling factor F of the Original Differential Evolution(ODE)algorithm,which can reduce the parameters of the algorithm and make it easy to use for engineers.Our algorithm was tested on 13 benchmark optimization problems with linear or/and nonlinear constraints and compared with other state-of-the-art evolutionary algorithms.The experimental results demonstrate that the performance of SIDE outperforms other evolutionary algorithms in terms of the quality of the final solution and the stability;and its computational cost(measured by the average number of fitness function evaluations)is lower than the cost required by the other techniques compared.