An application of infinite horizon stochastic dynamic programming in multi-stage project investment decision-making. (1st January 2012)

• Record Type: Journal Article
• Authors: Noor-E-Alam, Md.; Doucette, John
• Is Part Of: International journal of operational research. Volume 13:Number 4(2012)
• Page Start: 423
• Page End: 438
• Publication Date: 2012-01-01
• Subjects: project investment decision-making -- ROI -- return on investment -- uncertainty -- stochastic dynamic programming -- IHSDP -- infinite horizon stochastic dynamic programming; Operations research -- Periodicals; 003.05
• DOI: 10.1504/IJOR.2012.046226
• Languages: English
• ISSNs: 1745-7645

Abstract

In multi-stage project investment decision-making with uncertainty, risk mitigation plays a vital role. The return on investment (ROI) that will be realised in making a particular decision quite often carries a high degree of uncertainty, with an increased number of competing investors entering to the market every day. In this research, our objective is to develop a technique for a multi-stage project investment decision problem that deals with uncertainty in ROI and complex interrelated state transition dynamics. We do this by formulating our problem as an infinite horizon stochastic dynamic programming (IHSDP) problem and solve it to maximise the total return over an infinite time horizon. We have implemented our solution to the project investment decision problem in a simple case study using three well-known stochastic dynamic programming algorithms. Our simulation results show that the IHSDP algorithms are useful in making optimum investment decisions in an uncertain business environment.