最大独立集的图顶点搜索软件项目改进

O.O. Slabospitska, P. Stetsyuk, O. Khomiak
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引用次数: 0

摘要

对软件项目的需求是固定的,通过为软件项目管理任务量身定制的经典图形离散优化问题,通过技术方法中的最佳实践,通过技术描述性和规范性项目管理方法的无缝集成来增强软件项目。提出了一类软件项目管理任务,以演示这种集成的好处。研究了搜索最大独立集的两个布尔线性规划问题(第1节)和搜索所有可能的最大独立集的算法(第2节)。第3节给出了搜索给定数量的非相交独立集的问题陈述,这些独立集具有最大顶点数之和。在此基础上,描述了用最少颜色数对图顶点上色的Vizing-Plesnevich算法。为了解决布尔问题,使用了专门的数学编程语言AMPL和相应的求解程序gu- robi。对于所开发的基本算法,给出了参考AMPL代码版本及其运行结果。在第4节中考虑了使用所阐述的算法增强软件项目的说明性示例,即:25个专家在他们之前的项目中被划分为软件项目组合的连贯的无冲突子团队;关键软件系统中可重用组件的自主测试进度优化为关键软件项目中的独立团队组成的核心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximum independent sets of graph vertices searching for software projects improvement
The need is fixed to software project enhancing with seamless integration of technological-descriptive and normative project manage- ment approaches by means of classical Graph Discrete Optimization Problems tailoring for software project management tasks, poorly equipped with best practices within technological approach. Class of software project management tasks is proposed to demonstrate the benefits of such integration. Two Boolean linear programming problems are investigated for searching some maximum size indepen- dent set (Section 1) and an algorithm for searching all possible maximum size independent sets (Section 2). Section 3 presents Problem Statement for searching a given number of non-intersecting independent sets with maximum sum of vertices’ numbers within independent sets. Based on it, Vizing-Plesnevich algorithm is described for coloring the graph vertices with the minimum number of colors. To solve Boolean problems, both specialized mathematical programming language AMPL and corresponding solver program named gu- robi are used. For basic algorithms developed, reference AMPL code versions are given as well as their running results. Illustrative examples of software project enhancing with the algorithms elaborated are considered in Section 4, namely: 25 specialists being conflicted during their previous projects partitioning into coherent conflict-free sub-teams for software projects portfolio; schedule optimization for autonomous testing of reusable components within a critical software system; cores composing for independent teams in a critical software project.
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