Optimal planning of technology roadmap under uncertainty

Abstract

The selection and planning of technical projects is an important and challenging investment decision for companies as significant amount of capital is often involved. With the growing complexity and scale, managing technical research projects and technology roadmap (TRM) are greatly affected by uncertainties than ever before. However, existing approaches for addressing these problems are restricted to deterministic environments. In this study, a general methodology based on graph theory and mathematical programming for R&D projects planning subject to uncertainty is proposed to maximize profit and to find precedence relations according to technological trends for given budgets and time. We first put forward a new graph model and its mathematical definition to represent the relations among technologies. The network contains nodes to represent technologies and edges to denote feasible paths between two technology nodes. To deal with uncertainty, a network-based novel robust optimization model as well as a chance constrained model is developed. Finally, we apply the proposed model and solution approach to the TRM of Smart Home industry. The numerical study shows that the proposed method can effectively and efficiently solve the optimization problems for technical project planning, path designing, and project management, under uncertainty.