A Multiobjective Optimization Framework for Stochastic Control of Complex Systems

Conference · Thu Jan 01 00:00:00 EST 2015

OSTI ID:1185344

Malikopoulos, Andreas ^[1]; Maroulas, Vasileios ^[1]; Xiong, Professor Jie ^[2]

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1. ORNL
2. The University of Tennessee

This paper addresses the problem of minimizing the long-run expected average cost of a complex system consisting of subsystems that interact with each other and the environment. We treat the stochastic control problem as a multiobjective optimization problem of the one-stage expected costs of the subsystems, and we show that the control policy yielding the Pareto optimal solution is an optimal control policy that minimizes the average cost criterion for the entire system. For practical situations with constraints consistent to those we study here, our results imply that the Pareto control policy may be of value in deriving online an optimal control policy in complex systems.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
• Sponsoring Organization: USDOE Laboratory Directed Research and Development (LDRD) Program
• DOE Contract Number: DE-AC05-00OR22725
• OSTI ID: 1185344
• Resource Relation: Conference: The 2015 American Control Conference, Chicago, IL, USA, 20150701, 20150703
• Country of Publication: United States
• Language: English

Related Subjects

Complex systems
stochastic optimal control
controlled Markov chains
multicriteria optimization