打破平衡局面：通过自适应偏置提高平衡分频器的探索能力（CS NE）---刘持诚

在遗传算法（GA）中使用平衡交叉算子确保了作为子代产生的二进制字符串具有与父代相同的汉明权重，这在某些离散优化问题中是一种约束，是某些离散优化问题中需要寻求的约束。虽然这种方法减小了搜索空间的大小，但所产生的适配图往往会使 GA 探索和发现最优解变得更加困难。本文通过对这一问题进行了研究，将一种自适应偏置策略应用于基于反杂交算子的自适应偏置策略，在整个演化过程中，引入一定概率的非平衡性的子代，而且非平衡性会降低。实验表明，用这种自适应偏置策略改进搜索空间的探索，在平衡非线性布尔函数问题最优解的数量上，对 GA 的性能是有利的。

原文题目：Tip the Balance: Improving Exploration of Balanced Crossover Operators by Adaptive Bias

原文：The use of balanced crossover operators in Genetic Algorithms (GA) ensures that the binary strings generated as offsprings have the same Hamming weight of the parents, a constraint which is sought in certain discrete optimization problems. Although this method reduces the size of the search space, the resulting fitness landscape often becomes more difficult for the GA to explore and to discover optimal solutions. This issue has been studied in this paper by applying an adaptive bias strategy to a counter-based crossover operator that introduces unbalancedness in the offspring with a certain probability, which is decreased throughout the evolutionary process. Experiments show that improving the exploration of the search space with this adaptive bias strategy is beneficial for the GA performances in terms of the number of optimal solutions found for the balanced nonlinear Boolean functions problem.

原文作者：Luca Manzoni, Luca Mariot, Eva Tuba

原文地址：https://arxiv.org/abs/2004.11331