On Generating Random Graphs Based on Fuzzy Proximity Relationships between Vertices

Mohamed Amine Omrani, Wady Naanaa
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Abstract

Uncertain graphs are getting more and more important. They allow to tackle fuzzy situations in numerous frameworks. This paper investigates the issue of generating random graphs based on uncertain proximity relationships between vertices and the goal is to construct the most likely graph. The Constraint Programming paradigm was used to provide a systematic way to release uncertain graphs while maximizing and minimizing the paths that separate certain vertex pairs. The proposed approach allowed to generate uncertain graphs at a reasonable time. This is confirmed by experimental results obtained from a series of tests on several instances. Our solution lays the basis for further real world applications in different fields, such as analytical chemistry, telecommunication networks, and civil engineering.
基于点间模糊接近关系的随机图生成
不确定图变得越来越重要。它们允许在许多框架中处理模糊的情况。本文研究了基于顶点之间不确定接近关系的随机图的生成问题,其目标是构造最可能的图。使用约束规划范式提供了一种系统的方法来释放不确定图,同时最大化和最小化分离某些顶点对的路径。该方法允许在合理的时间内生成不确定图。在若干实例上进行的一系列试验结果证实了这一点。我们的解决方案为进一步在不同领域的实际应用奠定了基础,例如分析化学、电信网络和土木工程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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