Department of Statistics, Govt. College Khayaban-e-Sir Syed, Rawalpindi, Pakistan.
Department of Applied Mathematics & Statistics, Institute of Space Technology, Islamabad, Pakistan.
PLoS One. 2022 Sep 9;17(9):e0274456. doi: 10.1371/journal.pone.0274456. eCollection 2022.
A round-robin tournament is a contest where each and every player plays with all the other players. In this study, we propose a round-robin based tournament selection operator for the genetic algorithms (GAs). At first, we divide the whole population into two equal and disjoint groups, then each individual of a group competes with all the individuals of other group. Statistical experimental results reveal that the devised selection operator has a relatively better selection pressure along with a minimal loss of population diversity. For the consisting of assigned probability distribution with sampling algorithms, we employ the Pearson's chi-square and the empirical distribution function as goodness of fit tests for the analysis of statistical properties analysis. At the cost of a nominal increase of the complexity as compared to conventional selection approaches, it has improved the sampling accuracy. Finally, for the global performance, we considered the traveling salesman problem to measure the efficiency of the newly developed selection scheme with respect to other competing selection operators and observed an improved performance.
循环赛是一种每个选手都要与其他选手比赛的竞赛。在这项研究中，我们为遗传算法 (GA) 提出了一种基于循环赛的锦标赛选择算子。首先，我们将整个群体分为两个相等且不相交的组，然后每个组的个体与另一个组的所有个体竞争。统计实验结果表明，设计的选择算子具有相对较好的选择压力，同时人口多样性的损失最小。对于分配概率分布和抽样算法的组成，我们使用 Pearson 的卡方和经验分布函数作为拟合优度检验，以分析统计性质分析。与传统的选择方法相比，它的复杂度略有增加，但提高了抽样精度。最后，对于全局性能，我们考虑了旅行商问题，以衡量新开发的选择方案相对于其他竞争选择算子的效率，并观察到性能有所提高。
