Soft computing approach for VLSI Mincut partitioning: The state of the arts

Abstract

Recent research shows that the partitioning of VLSI-based system plays a very important role in embedded system designing. There are several partitioning problems that can be solved at all levels of VLSI system design. Moreover, rapid growth of VLSI circuit size and its complexity attract the researcher to design various efficient partitioning algorithms using soft computing approaches. In VLSI partitioning, netlist is used to optimize the parameters like mincut, power consumption, delay, cost, and area of the partitions. Hence, the Genetic Algorithm is a soft computational meta-heuristic method that has been applied to optimize these parameters over the past two decades. Here in this paper, we have summarized important schemes that have been adopted in Genetic Algorithm for optimizing one particular parameter, called mincut, to solve the partitioning problem.