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EPSRC Reference: GR/K03043/01
Title: A MATHEMATICAL PROGRAMMING APPROACH TO THE OPTIMAL SCHEDULING CONTROL OF STOCHASTIC SYSTEMS.
Principal Investigator: Glazebrook, Professor KD
Other Investigators:
McDiarmid, Professor C
Researcher Co-Investigators:
Project Partners:
Department: Mathematics and Statistics
Organisation: Newcastle University
Scheme: Standard Research (Pre-FEC)
Starts: 07 November 1994 Ends: 06 August 1998 Value (£): 122,167
EPSRC Research Topic Classifications:
Mathematical Aspects of OR
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
There is a pressing need for alternatives to the standard dynamic programming approach to problems concerning optimal scheduling control in stochastic systems. An alternative approach which charaterises the performance space of the system and then solves a mathematical programming problem on this space has recently been advanced by Bertsimas and Nino-Mara (BNM) who have derived a generalised Gittins index by this route. The project will seek both to explore the relationship of BNM's work to existing Gittins index theory and to further realise the clear potential of the mathematical programming approach.Extended (contra-) polymatroids (EP) and generalised conservation laws (GCL) are both fundamental to BNM's work. EP is a structure about which we know, as yet, very little. Foundational objectives of the project will be the elucidation of helpful characterisations of EP's and an expansion of the repertoire of systems known to satisfy GCL's. With these in place, we shall use the mathematical programming approach to advance Gittins index theory by, inter alia, exploring system indexability within this new framework and by developing LP-based sensitivity analysis for indexible systems. We shall also develop algorithms for control problems whose objective is nonlinear but whose performance space remains an EP. We shall seek to obtain efficient computational implementation of all algorithms developed.
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Organisation Website: http://www.ncl.ac.uk