Tuning Genetic Algorithm Parameters for Placement of Integrated Circuit Cells

Possibilities of reducing the problem of placement of integrated circuit (IC) elements to quadratic assignment problem and applying genetic algorithms to its matrix solution are observed in this paper. The impact of key parameters in genetic algorithms on the efficiency of solving the placement problem for IC cells have been studied. Based on these studies, recommendations are provided for selecting values and mechanisms for crucial parameters in genetic algorithms, such as population size, selection, crossover, and termination. In this paper, the problem of placement of IC elements is brought to the problem of quadratic assignment problem and generic algorithm with its adaptation to matrix solution of the problem of quadratic assignment has been implemented. The paper presents analysis results on the effectiveness of the proposed approach and compares it with the traditional method of sequential placement, utilizing examples of placing elements from various test circuits.