(2001) Adaptive Bias Simulated Evolution Algorithm for Placement. In: IEEE 2001 International Symposium on Circuits and Systems, Sydney, Australia.
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Abstract
Simulated Evolution (SE) is a general meta-heuristic for combinatorial optimization problem. A new solution is eveolved from current solution by relocating some of the solution elements. Elements with lower goodnesses have higher probabilities of getting selected for perturbation. Because it is not possible to accurately estimate the goodness of indivisual elements, SE resorts to a Selection Bias parameter. This parameter has major impact on the algorithm run-time and the quality of the solution subspace searched. In this work, we propose an adaptive bias scheme which adjusts automatically to the quality of solution and makes the algorithm run-time and the quality of the solution subspace searched. In this work, we propose an adaptive bias scheme which adjusts automatically to the quality of solution and makes the algorithm independent of the problem class or instance, as well as any user defined value. Experimental results on benchmark tests show major speedup while maintaining similar quality.
| Item Type: | Conference or Workshop Item (Other) |
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| Subjects: | Computer |
| Department: | College of Computing and Mathematics > Computer Engineering |
| Depositing User: | AbdulRahman |
| Date Deposited: | 25 Feb 2008 13:00 |
| Last Modified: | 01 Nov 2019 13:22 |
| URI: | http://eprints.kfupm.edu.sa/id/eprint/115 |