On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
A new algorithm for floorplan design
DAC '86 Proceedings of the 23rd ACM/IEEE Design Automation Conference
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
DAC '82 Proceedings of the 19th Design Automation Conference
Evolutionary algorithms for VLSI multi-objective netlist partitioning
Engineering Applications of Artificial Intelligence
VLSI module placement based on rectangle-packing by the sequence-pair
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Fuzzy set theory is a powerful and robust mathematical framework to handle many optimization problems. Floorplanning is an important step in the physical design of VLSI circuits, whose goal is to optimize the layout of the chip. With the development of IC designs, more and more issues need to be considered. As a multi-objective optimization problem (MOP), it is very difficult for floorplanning to balance various objectives simultaneously using traditional linear weighted penalty function. To overcome this problem, fuzzy rules and membership function are employed to combine various objectives in this paper. It is a convenient method of combining conflicting objectives and expert human knowledge. Experimental results show that this approach is stable and efficient which can obtain encouraging results in shorter time. Through the experimental results, we can have an intuitive understanding of objectives with various changes in parameter settings. This method can also be extended to handle other large scale MOP problems.