Project Details
| Short title | Evolutionary Approximation Algorithms for Optimisation: Algorithm Design and Complexity Analysis |
|---|---|
| Status | Finished |
| Effective start/end date | 29/04/11 → 28/10/15 |
Funding
- Engineering & Physical Science Research Council
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Average Drift Analysis and Population Scalability
He, J. & Yao, X., Jun 2017, In: IEEE Transactions on Evolutionary Computation. 21, 3, p. 426-439 26 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile8 Citations (Scopus)168 Downloads (Pure) -
Dynamic selection of evolutionary operators based on online learning and fitness landscape analysis
Consoli, P. A., Mei, Y., Minku, L. L. & Yao, X., Oct 2016, In: Soft Computing. 20, 10, p. 3889–3914Research output: Contribution to journal › Article › peer-review
Open AccessFile12 Citations (Scopus)300 Downloads (Pure) -
Estimation of the Distribution Algorithm With a Stochastic Local Search for Uncertain Capacitated Arc Routing Problems
Wang, J., Tang, K., Lozano, J. & Yao, X., 1 Feb 2016, In: IEEE Transactions on Evolutionary Computation. 20, 1, p. 96-109Research output: Contribution to journal › Article › peer-review
39 Citations (Scopus)