In this paper, we revisit the application of Genetic Algorithm (GA) to the Traveling Salesperson Problem (TSP) and introduce a family of novel crossover operators that outperform the previous state of the art. The novel crossover operators aim to exploit symmetries in the solution space, which allows us to more effectively preserve well-performing individuals, namely the fitness invariance to circular shifts and reversals of solutions. These symmetries are general and not limited to or tailored to TSP specifically.

翻译：本文重新审视了遗传算法（GA）在旅行商问题（TSP）中的应用，并引入了一系列性能超越现有最优方法的新型交叉算子。该新型交叉算子旨在利用解空间中的对称性——即解的环移与反转操作下的适应度不变性——从而更有效地保留高适应度个体。这些对称性具有普适性，并非局限于或专门针对TSP设计。