| EPSRC Reference: |
EP/F044895/1 |
| Title: |
Investigating Robust and Stochastic Optimisation Methods For Automated Container Terminals |
| Principal Investigator: |
Bell, Professor M |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Civil & Environmental Engineering |
| Organisation: |
Imperial College London |
| Scheme: |
Standard Research |
| Starts: |
01 May 2008 |
Ends: |
30 June 2011 |
Value (£): |
533,367
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| EPSRC Research Topic Classifications: |
| Transport Ops & Management |
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| EPSRC Industrial Sector Classifications: |
| Transport Systems and Vehicles |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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06 Feb 2008
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Engineering Systems Panel
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Announced
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Summary on Grant Application Form |
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The port industry plays a strategic role in the UK economy. There has been growing interest, particularly from European ports, in the automation of container terminals as a way to improve their efficiency and reliability. Plans for the new London Gateway container terminal on the former Shell Haven site envisage the highest degree of automation to date, providing a unique opportunity for the UK to develop strategically important expertise in automation software. This proposal seeks to develop innovative approaches based on robust and stochastic optimisation methods to control the automated horizontal and vertical movement of containers within the terminal and the implementation of these methods in prototype control software. Robust optimisation involves the definition of intervals for key parameters, like the start time and duration for container movements, and then looks for a solution that minimises maximum regret with respect to realisations of parameters. The optimisation takes future events into account through a rolling planning horizon. As an alternative to robust optimisation, stochastic optimisation deals with the uncertainty via a scenario analysis. In this approach, the uncertainty related to system components / parameters is modelled by a number of scenarios (or sub-problems) derived from an underlying optimization problem and the information structure can be represented as a tree, with each scenario corresponding to a path from the root of the tree out to a leaf. As both the robust and stochastic optimisation problems are in general NP-hard, heuristic methods will be devised to allow implementation in real time. The prototype control software will be tested in simulation before being made available to UK port operators.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.imperial.ac.uk |