Research Summaries

Back Optimization of Complex Systems

Fiscal Year 2011
Division Graduate School of Operational & Information Sciences
Department Operations Research
Investigator(s) Royset, Johannes O.
Sponsor Air Force Office of Scientific Research (Air Force)
Summary Military and civilian decision makers are often faced with the question of how to best design and operate complex systems under uncertainty. The resulting design optimization problem (DOP) may be defined on an infinite-dimensional space and involve risk measures expressed by expectations and max-function is, system models given in terms of differential equations, and disturbances not fully quantified by probability distributions. Consequently, DOP is rarely tractable by standard optimization algorithms and may require approximations. We propose to carry out a fundamental study of optimization in the presence of such approximations with focus on problem instances arising in engineering design and military mission planning. Specifically, we consider three related aspects: (i) We aim to construct tractable and conservative approximations of DOP using alternative risk measures. (ii) We propose to study the rate of convergence of approximation-based algorithms towards a solution of DOP. (iii) We plan to construct online precision-control policies that specify efficient approximation levels for algorithms during solution of DOP. The results of this study will enhance understanding of approximations in optimization algorithms, assist in the development of implementable algorithms for DOP, and enable efficient decision making in the presence of uncertainty and approximations.
Keywords Optimization Theory and Algorithms
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal