Title: An application of infinite horizon stochastic dynamic programming in multi-stage project investment decision-making

Authors: Md. Noor-E-Alam; John Doucette

Addresses: Department of Mechanical Engineering, University of Alberta, Edmonton AB T6G 2G8, Canada ' Department of Mechanical Engineering, University of Alberta, Edmonton AB T6G 2G8, Canada

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.

Keywords: project investment decision making; ROI; return on investment; uncertainty; stochastic dynamic programming; IHSDP; infinite horizon SDP; risk mitigation; investment decisions.

DOI: 10.1504/IJOR.2012.046226

International Journal of Operational Research, 2012 Vol.13 No.4, pp.423 - 438

Published online: 04 Mar 2012 *

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