Sushil J. Louis
Dept. of Computer Science
University of Nevada
Reno, NV 89557
sushil@cs.unr.edu
http://www.cs.unr.edu/ sushil
This paper presents a new approach to genetic algorithm based design. We use genetic algorithms augmented with a case-based memory of past design problem solving attempts to obtain better performance over time on sets of similar design problems. Rather than starting anew on each design, we periodically inject a genetic algorithm's population with appropriate intermediate design solutions to similar, previously solved problems. Experimental results on a configuration design problem; the design of a parity checker circuit, demonstrate the performance gains from our approach and show that our system learns to take less time to provide quality solutions to a new design problem as it gains experience from solving other similar design problems.
Content Areas: Configuration Design, Genetic Algorithms, Case-Based Reasoning.