一种应用于涉及顶点子集的图问题的遗传算法

Yaser Alkhalifah, R. L. Wainwright
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引用次数: 21

摘要

许多图问题寻求顶点的子集,以最大化或最小化顶点上的目标函数。其中有容化p中值问题、几何连通支配集问题、容化k中心问题和旅游游客问题。在此领域先前的遗传算法研究是通过随机替换对等位基因进行简单的突变。最近,一种被称为超突变的增强算子被开发出来,被证明是非常有效的解决容能p中值问题。我们提出了一种新的启发式算法,称为最近邻启发式(N4N),用于解决需要一个顶点子集的图问题。它是超突变算子的扩展。将使用这三种突变操作符(简单、超突变、N4N)的遗传算法应用于上面列出的四个图子集问题的实例。结果表明,在每个测试用例中,我们的N4N启发式算法都获得了优于超突变算子和简单突变算子的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A genetic algorithm applied to graph problems involving subsets of vertices
Many graph problems seek subsets of their vertices that maximize or minimize objective functions on the vertices. Among these are the capacitated p-median problem, the geometric connected dominating set problem, the capacitated k-center problem, and the traveling tourist problem. Prior genetic algorithms research in this area applied a simple mutation of an allele by random replacement. Recently an enhanced operator called hypermutation was developed, proving to be very effective for solving the capacitated p-median problem. We propose a GA with a new heuristic called the nearest four neighbors heuristic (N4N) for solving graph problems requiring a subset of vertices. It is an extension of the hypermutation operator. Genetic algorithms that use each of these three mutation operators (simple, hypermutation, N4N) are applied to instances of the four graph-subset problems listed above. Results show that our N4N heuristic obtained superior results compared to the hypermutation and the simple mutation operators in every test case.
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