Contreras-Bolton Carlos, Parada Victor
Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile.
PLoS One. 2015 Sep 14;10(9):e0137724. doi: 10.1371/journal.pone.0137724. eCollection 2015.
Genetic algorithms are powerful search methods inspired by Darwinian evolution. To date, they have been applied to the solution of many optimization problems because of the easy use of their properties and their robustness in finding good solutions to difficult problems. The good operation of genetic algorithms is due in part to its two main variation operators, namely, crossover and mutation operators. Typically, in the literature, we find the use of a single crossover and mutation operator. However, there are studies that have shown that using multi-operators produces synergy and that the operators are mutually complementary. Using multi-operators is not a simple task because which operators to use and how to combine them must be determined, which in itself is an optimization problem. In this paper, it is proposed that the task of exploring the different combinations of the crossover and mutation operators can be carried out by evolutionary computing. The crossover and mutation operators used are those typically used for solving the traveling salesman problem. The process of searching for good combinations was effective, yielding appropriate and synergic combinations of the crossover and mutation operators. The numerical results show that the use of the combination of operators obtained by evolutionary computing is better than the use of a single operator and the use of multi-operators combined in the standard way. The results were also better than those of the last operators reported in the literature.
遗传算法是受达尔文进化论启发的强大搜索方法。迄今为止，由于其特性易于使用且在为难题找到良好解决方案方面具有鲁棒性，它们已被应用于许多优化问题的求解。遗传算法的良好运行部分归功于其两个主要的变异算子，即交叉算子和变异算子。通常，在文献中，我们发现使用的是单一的交叉和变异算子。然而，有研究表明使用多个算子会产生协同作用，并且这些算子相互补充。使用多个算子并非易事，因为必须确定使用哪些算子以及如何将它们组合起来，而这本身就是一个优化问题。本文提出，可以通过进化计算来完成探索交叉和变异算子不同组合的任务。所使用的交叉和变异算子是通常用于解决旅行商问题的那些算子。寻找良好组合的过程是有效的，产生了交叉和变异算子的合适且协同的组合。数值结果表明，使用通过进化计算获得的算子组合比使用单一算子以及以标准方式组合的多个算子更好。结果也优于文献中报道的最新算子的结果。
