Maximizing the expected net present value of a project with phase-type distributed activity durations: An efficient globally optimal solution procedure

Stefan Creemers
Additional contact information
Stefan Creemers: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

Post-Print from HAL

Abstract: We study projects with activities that have stochastic durations that are modeled using phase-type distributions. Intermediate cash flows are incurred during the execution of the project. Upon completion of all project activities a payoff is obtained. Because activity durations are stochastic, activity starting times cannot be defined at the start of the project. Instead, we have to rely on a policy to schedule activities during the execution of the project. The optimal policy schedules activities such that the expected net present value of the project is maximized. We determine the optimal policy using a new continuous-time Markov chain and a backward stochastic dynamic program. Although the new continuous-time Markov chain allows to drastically reduce memory requirements (when compared to existing methods), it also allows activities to be preempted; an assumption that is not always desirable. We prove, however, that it is globally optimal not to preempt activities if cash flows are incurred at the start of an activity. Moreover, this proof holds regardless of the duration distribution of the activities. A computational experiment shows that we significantly outperform current state-of-the-art procedures. On average, we improve computational efficiency by a factor of 600, and reduce memory requirements by a factor of 321.

Keywords: Project scheduling; Project management; NPV maximization; SNPV; Stochastic activity durations (search for similar items in EconPapers)
Date: 2018-05-16
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Published in European Journal of Operational Research, 2018, 267 (1), pp.16-22. ⟨10.1016/j.ejor.2017.11.027⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02572114

DOI: 10.1016/j.ejor.2017.11.027

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().