GraphCombEx：一个探索大型图的组合优化性质的软件工具
GraphCombEx: A Software Tool for Exploration of Combinatorial Optimisation Properties of Large Graphs
摘要：
我们提出了一个原型的软件工具，用于探索在大型现实世界和合成复杂网络的多个组合优化问题。我们的工具，称为GraphCombEx（图组合资源管理器的首字母缩写），提供了一个统一的框架，可扩展的计算和高质量的次优解决方案和边界的一些广泛研究的组合优化问题的介绍。在其设计中特别考虑了对大规模图和复杂网络的有效表示和适用性。目前支持的问题包括最大团、图着色、最大独立集、最小顶点团覆盖、最小支配集以及最长简单圈问题。次优的解决方案和最佳目标值的区间估计使用可扩展的算法。该工具在设计时考虑到了可扩展性，考虑到未来将添加的进一步问题以及新的快速和高性能的算法。GraphCombEx已经在最近的一些研究中成功地用作支持工具，这些研究使用组合优化来分析复杂网络，这表明它作为研究软件工具的前景。
英文摘要：
We present a prototype of a software tool for exploration of multiple combinatorial optimisation problems in large real-world and synthetic complex networks. Our tool, called GraphCombEx (an acronym of Graph Combinatorial Explorer), provides a unified framework for scalable computation and presentation of high-quality suboptimal solutions and bounds for a number of widely studied combinatorial optimisation problems. Efficient representation and applicability to large-scale graphs and complex networks are particularly considered in its design. The problems currently supported include maximum clique, graph colouring, maximum independent set, minimum vertex clique covering, minimum dominating set, as well as the longest simple cycle problem. Suboptimal solutions and intervals for optimal objective values are estimated using scalable heuristics. The tool is designed with extensibility in mind, with the view of further problems and both new fast and high-performance heuristics to be added in the future. GraphCombEx has already been successfully used as a support tool in a number of recent research studies using combinatorial optimisation to analyse complex networks, indicating its promise as a research software tool.
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