Title
Understanding simulation solutions to resource constrained project scheduling problems with stochastic task durations
Abstract
The project scheduling problem domain is an important research and applications area of engineering management. Recently introduced project scheduling software such as Risk+, @Risk for Project, SCRAM and Risk Master have facilitated the use of simulation to solve project scheduling problems with stochastic task durations. Practitioners, however, should be made aware that the solution algorithm used in these software systems is based on the implicit assumption of perfect information, an assumption that jeopardizes the feasibility of solution results. This paper discusses the impact of assuming perfect information, introduces a multi-period stochastic programming based model of the project scheduling problem with stochastic task durations, and presents an alternative simulation algorithm that does not assume the availability of perfect information. A simple case study is used to illustrate the practical implications of applying simulation to address project scheduling problems with stochastic task durations. © Taylor & Francis.
Publication Date
1-1-1998
Publication Title
EMJ - Engineering Management Journal
Volume
10
Issue
4
Number of Pages
5-13
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1080/10429247.1998.11415002
Copyright Status
Unknown
Socpus ID
0032273138 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0032273138
STARS Citation
Fernandez, Abel A.; Armacost, Robert L.; and Pet-Edwards, Julia J., "Understanding simulation solutions to resource constrained project scheduling problems with stochastic task durations" (1998). Scopus Export 1990s. 3302.
https://stars.library.ucf.edu/scopus1990/3302