This paper proposed a new crossover operator called the Logistic crossover (LogX) which is used in conjunction with a well-known mutation operators Makinen, Periaux and Toivanen mutation (MPTM), non-uniform mutation (NUM) and power mutation (PM). The defined algorithm used the real encoded crossover and mutation operator. A set of 15 test problems have been taken from global optimization literature to test the performance of the proposed algorithm. Results are compared with some popular genetic algorithms (GAs) existing in the literature. The evaluation of performance of the proposed algorithm has been done by analysing the mean of the objective function values and by the Performance Index (PI). This comparative study shows that Logistic crossover operator (LogX) with three mutation operators outperform the other crossover operators.

本文提出了一种称为Logistic交叉（LogX）的新交叉算子，该算子与著名的突变算子Makinen，Periaux和Toivanen突变（MPTM），非均匀突变（NUM）和幂突变（PM）结合使用。定义的算法使用了真正的编码交叉和变异算子。从全局优化文献中选取了15个测试问题来测试所提出算法的性能。将结果与文献中存在的一些流行遗传算法（GA）进行比较。通过分析目标函数值的均值和性能指数（PI），完成了所提出算法的性能评估。这项比较研究表明，具有三个突变算子的Logistic交叉算子（LogX）优于其他交叉算子。