Moments and distribution of the net present value of a serial project

Autor: Stefan Creemers
Přispěvatelé: Lille économie management - UMR 9221 (LEM), Université d'Artois (UA)-Université catholique de Lille (UCL)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2018
Předmět:
Technology
Mathematical optimization
Least cost fault detection problem
Information Systems and Management
General Computer Science
FLEXIBILITY
0211 other engineering and technologies
Social Sciences
02 engineering and technology
Management Science and Operations Research
01 natural sciences
Net present value
Industrial and Manufacturing Engineering
[SHS]Humanities and Social Sciences
010104 statistics & probability
Project management
Business & Economics
RESOURCE
NPV distribution
Limit (mathematics)
0101 mathematics
Duration (project management)
COMPLEX-SYSTEMS
ComputingMilieux_MISCELLANEOUS
Mathematics
Science & Technology
021103 operations research
Present value
business.industry
Operations Research & Management Science
RESEARCH-AND-DEVELOPMENT
Stochastic game
Management
Modeling and Simulation
[SHS.GESTION]Humanities and Social Sciences/Business administration
Project scheduling
Project portfolio management
business
Random variable
Zdroj: European Journal of Operational Research
European Journal of Operational Research, Elsevier, 2018, 267 (13), pp.835-848
HAL
European Journal of Operational Research, 2018, 267 (13), pp.835-848
ISSN: 0377-2217
1872-6860
Popis: © 2017 Elsevier B.V. We study the Net Present Value (NPV) of a project with multiple stages that are executed in sequence. A cash flow (positive or negative) may be incurred at the start of each stage, and a payoff is obtained at the end of the project. The duration of a stage is a random variable with a general distribution function. For such projects, we obtain exact, closed-form expressions for the moments of the NPV, and develop a highly accurate closed-form approximation of the NPV distribution itself. In addition, we show that the optimal sequence of stages (that maximizes the expected NPV) can be obtained efficiently, and demonstrate that the problem of finding this optimal sequence is equivalent to the least cost fault detection problem. We also illustrate how our results can be applied to a general project scheduling problem where stages are not necessarily executed in series. Lastly, we prove two limit theorems that allow to approximate the NPV distribution. Our work has direct applications in the fields of project selection, project portfolio management, and project valuation. ispartof: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH vol:267 issue:3 pages:835-848 status: published
Databáze: OpenAIRE
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