Infinite Horizon Optimization
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Kristen M. Biggar, N-BioS', 'PO_EMAI': None, 'PO_PHON': None}
This research considers the general stochastic infinite horizon                 optimization problem.  This sub-class of optimization problems                  includes most production-inventory, capacity expansion and equipment            replacement problems, as well as many others.  The proposed approach            has three steps:  (1)  Given the stochastic problem, determine when             there exists, and how to obtain, an equivalent deterministic problem,           where equivalent means having the same optimal solution as the adaptive         (closed-loop) solution to the stochastic problem; (2)  Given the                infinte horizon deterministic problem from above, determine when there          exists, and how to obtain, anequivalent finite horizon problem, where           equivalent means agreement in the initial decision; (3)  Determine how          to solve the finite horizon problem in an efficient manner.  Although           the equivalences in parts 1) and 2) need not always exist, preliminary          work suggests a wide class of practically interesting problems for              which this approach would be successful.
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{'Code': '1454', 'Text': 'SYSTEMS THEORY'}
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