Abstract: Efficient and high-accuracy parameter adjustment is performed by applying a genetic algorithm to a parameter adjustment such as a physical model of a transistor and so on. A parameter adjusting device includes a device generating new parameter genes by an initial population generating device and a special crossover processing by a Latin hyper square method. Also, a normalization device is provided for applying to parameters which are real numbers. Moreover, for example, to exactly meet a specific property of the transistor (MOSFET), an evaluation device which evaluates a parameter in consideration of a log scale, is provided. According to the above-mentioned structure, the genetic algorithm can be applied to the parameter adjustment with a large number of parameters such as the physical model of the transistor and so on, so that a parameter group can be determined with a high degree of accuracy within a short time.

Abstract: A chromosome using each of a plurality of parameters of a physical model of a semiconductor element as a gene is defined and the parameters are optimized using a genetic algorithm based on the characteristics measurement data of the semiconductor element fabricated by way of trial. In the selection processing of the genetic algorithm, a sum of a first evaluation value based on linear scale data and a second evaluation value based on logarithmic scale data is employed as the evaluation value of the chromosome.