One-Stage R&D Portfolio Optimization with an Application to Solid Oxide Fuel Cells
نویسندگان
چکیده
This paper provides an overview of the one-stage R&D portfolio optimization problem. It provides a novel problem model that can be solved with stochastic combinatorial optimization methods. Current solution methods are reviewed an a new method, Stochastic Gradient Portfolio Optimization (SGPO), is proposed. We proved global convergence under certain conditions. SGPO is numerically compared to current optimization methods on a test case involving Solid Oxide Fuel Cells.
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