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Stochastic Optimization Modeling and Quantitative Project Management

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3 Author(s)
Rao, U.S. ; Unisys Global Services India, Bangalore ; Kestur, S. ; Pradhan, C.

Successful projects manage and balance four variables effectively: schedule, effort (or cost), scope, and quality. Project activities influence these four variables as distributions rather than deterministically. Thus, the end results expected from a project with respect to those variables are a function of all the distributions associated with each activity. Integrating stochastic optimization modeling (SOM) with quantitative project management (QPM) lets projects factor in uncertainties and get near-real-time feedback, so they can monitor key variables and initiate corrective action.This case study provides a detailed description of our implementing SOM and QPM in a development project. Our project's scope was to develop a resource management application that facilitated centralized data collection with distributed reporting.

Published in:

Software, IEEE  (Volume:25 ,  Issue: 3 )