On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Estimation of average switching activity in combinational and sequential circuits
DAC '92 Proceedings of the 29th ACM/IEEE Design Automation Conference
A survey of optimization techniques targeting low power VLSI circuits
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
VISI Physical Design Automation: Theory and Practice
VISI Physical Design Automation: Theory and Practice
Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Recursive Bi-Partitioning of Netlists for Large Number of Partitions
DSD '02 Proceedings of the Euromicro Symposium on Digital Systems Design
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Fuzzy biasless simulated evolution for multiobjective VLSI placement
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Multilevel cooperative search for the circuit/hypergraph partitioning problem
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Intelligent farmer agent for multi-agent ecological simulations optimization
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Multi-objective floorplanning based on fuzzy logic
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
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The problem of partitioning appears in several areas ranging from VLSI, parallel programming to molecular biology. The interest in finding an optimal partition, especially in VLSI, has been a hot issue in recent years. In VLSI circuit partitioning, the problem of obtaining a minimum cut is of prime importance. With current trends, partitioning with multiple objectives which includes power, delay and area, in addition to minimum cut is in vogue. In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). Fuzzy rules are incorporated in order to handle the multi-objective cost function. For SimE, fuzzy goodness functions are designed for delay and power, and proved efficient. A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. PowerFM performs better in terms of power dissipation for smaller circuits. For larger sized circuits, SimE outperforms PowerFM in terms of all the three objectives, delay, number of nets cut, and power dissipation.