Scheduling Projects with Stochastic Activity Duration to Maximize EPV

European Journal of Operational Research 198(3): 697-705 (2009)

Posted: 20 Sep 2007 Last revised: 26 Jun 2012

See all articles by Vera Tilson

Vera Tilson

University of Rochester - Simon Business School

Matthew J. Sobel

Weatherhead School of Management, Case Western Reserve University

Joseph G. Szmerekovsky

North Dakota State University - Department of Management, Marketing & Finance

Date Written: September 18, 2006

Abstract

Although uncertainty is rife in many project management contexts, little is know about adaptively optimizing project schedules. We formulate the problem of adaptively optimizing the expected present value of a project's cash flow, and we show that it is practical to perform the optimization. The formulation includes randomness in activity durations, costs, and revenues, so the optimization leads to a recursion with a large state space even if the durations are exponentially distributed. We present an algorithm that partially exorcises the "curse of dimensionality" as computational results demonstrate. Most of the paper is restricted to exponentially distributed task durations, but we sketch the adaptation of the algorithm to approximate any probability distribution of task duration.

Keywords: Project Management, Dynamic Programming/Optimal Control: Applications

Suggested Citation

Tilson, Vera and Sobel, Matthew J. and Szmerekovsky, Joseph G., Scheduling Projects with Stochastic Activity Duration to Maximize EPV (September 18, 2006). European Journal of Operational Research 198(3): 697-705 (2009). Available at SSRN: https://ssrn.com/abstract=1015785

Vera Tilson (Contact Author)

University of Rochester - Simon Business School ( email )

Rochester, NY 14627
United States

Matthew J. Sobel

Weatherhead School of Management, Case Western Reserve University ( email )

10900 Euclid Ave.
Cleveland, OH 44106-7235
United States

Joseph G. Szmerekovsky

North Dakota State University - Department of Management, Marketing & Finance ( email )

Fargo, ND 58105
United States

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