Abstract
AbstractThe valuation and planning of complex projects are becoming increasingly challenging with rising market uncertainty and the deregulation of many industries, which have also raised the need for efficient risk management. We take the perspective of a private firm interested in sequential capacity expansion of a project and develop a framework for measuring the downside risk of the serial project and optimising the sequence of the stages. Under general distributional assumptions for the duration of each stage, we present an accurate representation of the project’s net present value (NPV) distribution based on a Pearson curve fit, leading to closed-form expressions for the associated risk measures. We then assess the impact of duration variability on the value at risk and demonstrate its role in stochastic project scheduling. We also account for the trade-off between maximising the expected NPV and minimising the risk exposure, and obtain the optimal schedule for risk-averse decision-makers. It becomes obvious that both the duration variability of each stage and the decision-makers’ risk preferences can significantly affect the optimal sequence of the stages and that high duration variability is not always undesirable, even for risk-averse decision-makers.
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,Business, Management and Accounting (miscellaneous)
Reference67 articles.
1. Akhiezer NI (1965) The Classical moment problem and some related questions in analysis, University Mathematical Monographs. Oliver & Boyd, Edinburgh
2. Almond B, Remer RS (1979) Models for present-worth analysis of selected industrial cash flow patterns. Eng Process Econ 4(4):455–466
3. Alonso-Ayuso A, Carvallo F, Escudero LF, Guignard M, Pi J, Puranmalka R, Weintraub A (2014) Medium range optimization of copper extraction planning under uncertainty in future copper prices. Eur J Oper Res 233(3):711–726
4. Ashtiani B, Leus R, Aryanezhad M-B (2011) New competitive results for the stochastic resource-constrained project scheduling problem: exploring the benefits of pre-processing. J Sched 14(2):157–171
5. Baldwin CY, Clark KB, Clark KB et al (2000) Design rules: the power of modularity, vol 1. MIT Press, Cambridge
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献