当前位置: X-MOL 学术Evol. Comput. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
High-Order Entropy-based Population Diversity Measures in the Traveling Salesman Problem
Evolutionary Computation ( IF 6.8 ) Pub Date : 2020-12-01 , DOI: 10.1162/evco_a_00268
Yuichi Nagata 1
Affiliation  

To maintain the population diversity of genetic algorithms (GAs), we are required to employ an appropriate population diversity measure. However, commonly used population diversity measures designed for permutation problems do not consider the dependencies between the variables of the individuals in the population. We propose three types of population diversity measures that address high-order dependencies between the variables to investigate the effectiveness of considering high-order dependencies. The first is formulated as the entropy of the probability distribution of individuals estimated from the population based on an m-th--order Markov model. The second is an extension of the first. The third is similar to the first, but it is based on a variable order Markov model. The proposed population diversity measures are incorporated into the evaluation function of a GA for the traveling salesman problem to maintain population diversity. Experimental results demonstrate the effectiveness of the three types of high-order entropy-based population diversity measures against the commonly used population diversity measures.

中文翻译:

旅行商问题中基于高阶熵的人口多样性测度

为了保持遗传算法(GA)的种群多样性,我们需要采用适当的种群多样性措施。然而,为置换问题设计的常用种群多样性度量没有考虑种群中个体变量之间的依赖关系。我们提出了三种类型的种群多样性度量,用于解决变量之间的高阶依赖关系,以研究考虑高阶依赖关系的有效性。第一个公式表示为基于 m 阶马尔可夫模型从总体中估计的个体概率分布的熵。第二个是第一个的扩展。第三个与第一个类似,但它基于变阶马尔可夫模型。提出的人口多样性措施被纳入到旅行商问题的 GA 评估函数中,以保持人口多样性。实验结果证明了三种基于高阶熵的种群多样性措施对常用种群多样性措施的有效性。
更新日期:2020-12-01
down
wechat
bug