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2006
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Handling Constraints in Multi-Objective GA for Embedded System Design

10 years 7 months ago
Handling Constraints in Multi-Objective GA for Embedded System Design
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...
Biman Chakraborty, Ting Chen, Tulika Mitra, Abhik
Added 12 Jun 2010
Updated 12 Jun 2010
Type Conference
Year 2006
Where VLSID
Authors Biman Chakraborty, Ting Chen, Tulika Mitra, Abhik Roychoudhury
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