An approximate solution approach for a scenario-based capital budgeting model

Real options techniques such as contingent claims analysis and dynamic programming can be used for project evaluation when the project develops stochastically over time and the decision to invest into this project can be postponed. Following that perspective, Meier et al. (2001) presented a scenario based model that captures risk uncertainty and managerial flexibility, maximizing the time-varying of a portfolio of investment options. However, the corresponding linear integer program turns out to be quite intractable even for a small number of projects and time periods. In this paper, we propose a heuristic approach based on an alternative scenario based model involving a much less number of variables. The new approach allows the determination of reasonable quality approximate solutions with huge reductions on the computational times required for solving large size instances.