Simulated evolution algorithm for multiobjective VLSI netlist bi-partitioning

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 multiobjective 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

• Type: Conference
• Year: 2003
• Where: ISCAS
• Authors: Sadiq M. Sait, Aiman H. El-Maleh, Rush H. Al-Abuji
• Keywords: ISCAS 2003, Overall Multiobjective Cost, Simulated Evolution Algorithm, VLSI Netlist Bi-partitioning