一种新型的差分演化算法及其应用研究  

Application study on a novel differential evolution algorithm

作　　者：鄢靖丰[1] 张泊平[1] 龚文引[2] 谭水木[1] 

机构地区：[1]许昌学院计算机科学与技术学院,河南许昌461000 [2]中国地质大学计算机学院,武汉430074

出　　处：《计算机应用》2008年第3期719-722,725,共5页journal of Computer Applications

基　　金：河南省教育厅项目(07020065);许昌市科技计划项目(07020062)

摘　　要：提出了一种新的基于简单多样性规则的改进差分演化算法,并把它运用于约束全局最优化问题的求解中。新算法的特征是:1)提出一种新的混合自适应交叉变异算子,以增强算法的搜索能力;2)采用具有保持群体多样性的约束函数处理技术;3)简化基本差分演化算法的缩放因子,尽量减少算法的控制参数,方便工程人员的使用。通过对13个标准测试函数进行测试,并与其他演化算法结果进行比较。实验结果表明,新算法在求解精度和稳定性具有很好的性能,而且其函数平均评价次数要低于所比较的其他演化算法。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.

关 键 词：演化算法 差分演化算法 多样性规则 混合自适应交叉变异算子 约束全局最优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]