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This content will become publicly available on January 1, 2017

Title: A duality framework for stochastic optimal control of complex systems

In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derive online the optimal control policy in complex systems.
Authors:
 [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
OSTI Identifier:
1224740
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Automatic Control
Additional Journal Information:
Journal Volume: 1; Journal Issue: 1; Journal ID: ISSN 0018-9286
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING Complex Systems; Stochastic Optimal Control; Multiobjective Optimization; Pareto Efficiency; HEV optimization