One-stage R&D portfolio optimization with an application to solid oxide fuel cells

Lauren Hannah, Warren Buckler Powell, Jeffrey Stewart

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

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 and a new method that scales to large problems, Stochastic Gradient Portfolio Optimization (SGPO), is proposed. Although SGPO is a heuristic method, we prove global convergence in certain conditions. SGPO is numerically compared to current optimization methods on a test case involving Solid Oxide Fuel Cells.

Original languageEnglish (US)
Pages (from-to)141-163
Number of pages23
JournalEnergy Systems
Volume1
Issue number2
DOIs
StatePublished - May 1 2010

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Economics and Econometrics
  • Energy(all)

Keywords

  • R&D portfolio
  • Solid oxide fuel cell
  • Stochastic combinatorial optimization

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