Network-based real option models

Building on earlier work to incorporate real option methodologies into network modeling, two models are proposed. The first is the network option design problem, which maximizes the expanded net present value of a network investment as a function of network design variables with the option to defer the committed design investment. The problem is shown to be a generalized version of the network design problem and the multi-period network design problem. A heuristic based on radial basis functions is used to solve the problem for continuous link expansion with congestion effects. The second model is a link investment deferral option set, which decomposes the network investment deferral option into individual, interacting link or project investments. This model is a project selection problem under uncertainty, where each link or project can be deferred such that the expanded net present value is maximized. The option is defined in such a way that a lower bound can be solved using an exact method based on multi-option least squares Monte Carlo simulation. Numerical tests are conducted with the classical Sioux Falls network and compared to earlier published results.

Research highlights
► Proposed a formulation for network design problem that maximizes real option value.
► Proposed a lower bound formulation for decoupling a network design into a set of interacting project options for staging under uncertainty.
► Proposed a solution algorithm for obtaining the option value and staging solution for the set of interacting project options.
► Conducted a numerical test with Sioux Falls network to compare against earlier published results and demonstrate model capabilities.