EPSRC Reference: |
GR/N22649/01 |
Title: |
ALOGRITHMS FOR VARIATIONAL INEQUALITY PROBLEMS OPTIMAL SCHEDULING & OPTIMAL MODEL PREDICTIVE CONTROL |
Principal Investigator: |
Sargent, Professor R |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Chemical Engineering |
Organisation: |
Imperial College London |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 August 2000 |
Ends: |
31 July 2003 |
Value (£): |
174,119
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EPSRC Research Topic Classifications: |
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EPSRC Industrial Sector Classifications: |
Chemicals |
Information Technologies |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
Many physical problems can be formulated in terms of variational principles, while economic and distribution-network equilibria similarly give rise to variational inequality problems (VIP). Nonlinear programming is also a special case of VIP which thus also covers optimal design. We have recently devised an entirely new algorithm for solving VIPs and shown that on typical nonlinear test problems it is 5-10 times faster than current algorithms, enabling us to solve nonlinear problems substantially faster than current algorithms solve their linearised counterparts. This has wide implications for all nonlinear optimisation algorithms and there are several avenues to be explored which could lead to further significant improvement. First our prototype algorithm needs to be rewritten using sparse-matrix algorithms and to be interfaced to a process simulation package, making it available for solving largescale process design problems. Then the same ideas will be applied to our existing optimal control algorithm, making it available for offline studies and incorporation in an on-line optimal model predictive control package. Finally the ideas can be applied to our existing optimal scheduling package, again reducing solution times and enabling us to extend the package to handle nonlinear models for the individual tasks.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.imperial.ac.uk |