A Novel Multicriteria Optimization Technique for VLSI Floorplanning Based on Hybridized Firefly and Ant Colony Systems

In VLSI circuit design, physical design is one of the main steps in placing into chip area. Floorplanning a crucial step IC which generates blueprint for placement modules chip. A floorplanning accepts netlist as its input, given by circuit-partitioning design. The optimal placements modules. contains modules’ dimensions, size, and interconnect information. During floorplan generation, area, wire length required connecting heat generated chips can be estimated. good makes routing simple. order to improve performance minimizing length, peak temperature, it essential generate an optimized developing metaheuristic optimization algorithms. novel Hybridized Multicriteria Ant Colony Firefly Optimization (HMAC-FO) technique introduced floorplan. primary focus HMAC-FO model generating efficient floorplanning. standard MCNC benchmark dataset has number with their connections. algorithm HMAC-FO, been used thermal. firefly initially requires some solutions fireflies’ population. algorithm, usually, populations are randomly. But, algorithm’s obtain better optimum results, proposed uses ACO initial population, all solutions. set population globally result. experimented circuits, results prove that reduces area 3.48%, 0.64% temperature 3.33% than best existing methodology. methodology optimization, such generation.