不平衡连通子图问题

Shaohui Gong, Cheng Zhu, Luohao Tang, Xianqiang Zhu, Lianfei Yu
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引用次数: 1

摘要

一类决策和优化问题可以定义为在满足一定要求的情况下在图中找到连通的子图。本文研究不平衡连通子图问题,简称UBCS问题。给定一个节点属于不同类别的图,UBCS问题的目标是找到某一类节点的数量和比例分别满足给定要求的最大连通子图。这个问题在现实世界中有很多应用,例如,找到一个社交网络的最大子图,其中喜欢特定产品的人的比例不小于给定值。引入了UBCS问题的形式化定义,研究了UBCS问题的计算复杂度,证明了UBCS问题在平面图上是np困难的。提出了一种基于网络流的混合整数规划模型来表述这一问题。此外,设计了一种简单快速的启发式算法来解决大规模稀疏图中的UBCS问题。通过数值实验,验证了启发式算法的优缺点,并与IBM ILOG CPLXE优化求解器进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Unbalanced Connected Subgraph Problem
A large class of decision and optimization problems can be defined as finding a connected sub graph in a graph while satisfying certain requirements. This paper studies the Unbalanced Connected Subgraphs problem, referred to as UBCS problem. Given a graph with nodes belonging to different categories, the objective of UBCS problem is to find the maximum connected subgraph in which the number and proportion of nodes in certain categories can meet given requirements, respectively. This problem has many real-world applications, for example, to find the largest subgraph of a social network in which the proportion of people who likes a specific product is not less than a given value. This paper introduces the formal definition of UBCS problem, studies its computational complexity and proves that it is NP-hard in planar graphs. A mixed integer programming model based on network flow is proposed to formulate this problem. Moreover, a simple and fast heuristic algorithm is designed to solve UBCS problem in large-scale sparse graphs. Through numerical experiments, the advantages and disadvantages of the heuristic are verified and compared with the optimization solver IBM ILOG CPLXE.
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