通过机器学习和运筹学工具的灵活集成推进项目管理

Nikos Kanakaris, N. Karacapilidis, Alexis Lazanas
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引用次数: 7

摘要

项目管理是一项复杂的实践,它给世界各地的组织和专家带来了一系列挑战。为了推进这一实践,本文提出了一种基于当代机器学习和运筹学工具之间协同作用的混合方法。该方法将机器学习技术的预测导向与运筹学算法的规定性相结合。它可以帮助规划、监视和执行常见的PM任务,例如资源分配、任务分配和任务持续时间估计。通过两个实际例子证明了我们的方法的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Advancement of Project Management through a Flexible Integration of Machine Learning and Operations Research Tools
Project Management is a complex practice that is associated with a series of challenges to organizations and experts worldwide. Aiming to advance this practice, this paper proposes a hybrid approach that builds on the synergy between contemporary Machine Learning and Operations Research tools. The proposed approach integrates the predictive orientation of Machine Learning techniques with the prescriptive nature of Operations Research algorithms. It can aid the planning, monitoring and execution of common PM tasks such as resource allocation, task assignment, and task duration estimation. The applicability of our approach is demonstrated through two realistic examples.
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