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In this paper the Simulated Evolution algorithm (SimE) is engineered to solve the optimization problem of multi-objective VLSI netlist bi-partitioning. The multi-objective version of the problem is addressed in which, power dissipation, timing performance, as well as cut-set are optimized while Balance is taken as a constraint. Fuzzy rules are used in order to design the overall multi-objective cost function that integrates the costs of three objectives in a single overall cost value. Fuzzy goodness functions are designed for delay and power, and proved efficient. A series of experiments are performed to evaluate the efficiency of the algorithm. ISCAS-85/89 benchmark circuits are used and experimental results are reported and compared to earlier algorithms like GA and TS.
Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on (Volume:5 )
Date of Conference: 25-28 May 2003