Please use this identifier to cite or link to this item:
|Title:||Handling constraints in multi-objective GA for embedded system design|
|Authors:||Chakraborty, B. |
|Source:||Chakraborty, B.,Chen, T.,Mitra, T.,Roychoudhury, A. (2006). Handling constraints in multi-objective GA for embedded system design. Proceedings of the IEEE International Conference on VLSI Design 2006 : 305-310. ScholarBank@NUS Repository. https://doi.org/10.1109/VLSID.2006.95|
|Abstract:||Design space exploration is central to embedded system design. Typically this is a multi-objective search problem, where performance, power, area etc. are the different optimization criteria, to find the Pareto-optimal points. Multi-objective Genetic Algorithms (GA) have been found to be a natural fit for such searches and have been used widely. However, for certain design spaces, a large part of the space being explored by GA may violate certain design constraints. In this paper, we use a multi-objective GA algorithm based on "repair", where an infeasible design point encountered during the search is repaired to a feasible design point. Our primary novelty is to use a multi-objective version of search algorithms, like branch and bound, as the repair strategy to optimize the objectives. We also precompute a layout of the genes such that infeasible design points are less likely to be encountered during the search. We have successfully employed our hybrid search strategy to design application-specific instruction-set extensions that maximize performance and minimize area. © 2006 IEEE.|
|Source Title:||Proceedings of the IEEE International Conference on VLSI Design|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 5, 2017
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.