| EPSRC Reference: |
GR/R64742/01 |
| Title: |
A Rigorious Investigation into Estimation of Distribution Algorithms |
| Principal Investigator: |
Zhang, Professor Q |
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| Department: |
Computer Sci and Electronic Engineering |
| Organisation: |
University of Essex |
| Scheme: |
Fast Stream |
| Starts: |
28 March 2002 |
Ends: |
27 September 2003 |
Value (£): |
61,942
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Summary on Grant Application Form |
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Population-based algorithms using estimation of distribution, often called estimation of distribution algorithms (EDAs), have been recongnized as a major paradigm in evolutionary computation. Some EDA-like algorithms have achieved state-of-the-art performace in applications. However, most of the existing EDA-like algorithms have been developed based on an ad-hoc basis. Both theory and implementation in this area are far from complete. This project will work towards establishing a sound theory for characterizing and explaining EDA-like algorithms. We will extend our previous results and seek to obtain global convergence conditions for the factorized distribution algorithm and ant-colony optimization algorithms. With a better understanding of the working mechanisms of EDA-like algorithms, we will embed experimental design methods in EDA to develop more powerful and statistically sound search and optimization algorithms. We will also exploit the potential benefits of combining EDA-like algorithms with GLS (Guided Local Search). We will propose to use continuous optimization problems and quadratic assignment problems as our test problems.
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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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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.sx.ac.uk |