Stochastic Optimization Modeling and Quantitative Project Management

Authors:
Uma Sudhakar Rao;Srikanth Kestur;Chinmay Pradhan
Affiliations:
Unisys Global Services India;Unisys Global Services India;Unisys Global Services India
Venue:
IEEE Software
Year:
2008

Citing 0
Cited 2

Modelling software processes: a focus on objectives

Proceedings of the 24th ACM SIGPLAN conference companion on Object oriented programming systems languages and applications
Real-time business process monitoring method for prediction of abnormal termination using KNNI-based LOF prediction

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.01

Visualization

Abstract

A successful project effectively manages four cornerstones—schedule, cost, scope, and quality—to achieve its goals. Every project activity influences these four cornerstones. Stochastic optimization modeling factors in the uncertainties associated with project activities and provides insight into the expected project outputs as probability distributions rather than as deterministic approximations. Integrating stochastic optimization modeling with quantitative project management provides near-real-time feedback, enabling projects to monitor areas that induce maximum variability and thereby initiate corrective actions as required.