On the Advancement of Project Management through a Flexible Integration of Machine Learning and Operations Research Tools

被引：5

作者：

Kanakaris, Nikos ^{[1
]}

Karacapilidis, Nikos ^{[1
]}

Lazanas, Alexis ^{[1
]}

机构：

[1] Univ Patras, Ind Management & Informat Syst Lab, MEAD, Rion 26504, Greece

来源：

ICORES: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON OPERATIONS RESEARCH AND ENTERPRISE SYSTEMS | 2019年

关键词：

Project Management; Machine Learning; Operations Research; Intelligent Optimization; NEURAL-NETWORKS;

D O I：

10.5220/0007387103620369

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

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.

引用

页码：362 / 369

页数：8