Hedieh Ashrafi: Selection, Scheduling of Project Portfolios under profit uncertainty and limited available Scientists by using Adaptive Robust Optimization

We present a model for the selection and scheduling of R&D projects with several phases.The initial model contains two main stages development and commercialization. The goal of this model is to maximize the net present value under constraints of scientists' availability and uncertain profit. This nonlinear mixed-integer model is NP-hard and not tractable for large-scale problem instances where we use adaptive robust model, Hence, we develop a strong Mixed Integer Programming model and a heuristic algorithm. Then, we show the performance of these algorithms in terms of running time and optimality gap in experiments.