Method for optimizing two-layer embedded resistance layout by adopting fuzzy genetic algorithm

Abstract

The invention discloses a method for optimizing two-layer embedded resistance layout by adopting a fuzzy genetic algorithm. The method comprises the following steps: performing genetic operation on upper and lower layer resistance respectively; performing initial population generation, crossover, variation and evolution reversion operation in sequence; sharing crossover probability Pc and variation probability Pm output by a fuzzy logic controller; during calculation of a fitness function and local catastrophe, evaluating and updating by taking two populations as a whole; after population update, judging once again; if a certain condition is satisfied, performing local catastrophe on the populations. Compared with a method for performing thermal layout optimization by adopting a standard genetic algorithm, the method has the advantages that remarkable advantages are achieved on the aspects of keeping population variety and searching a globally optimal solution, and ANSYS temperature field distribution and the thermal imaging result of an experimental sample plate indicate that the maximum temperature and the maximum temperature difference are reduced greatly. A two-layer electronic element thermal layout rule obtained according to an optimization result is suitable for embedded resistance, and plays a guidance role in the thermal layout design of other electronic elements.

Description

technical field [0001] The invention relates to a resistance thermal layout, in particular to a method for optimizing a two-layer embedded resistance thermal layout by using a fuzzy genetic algorithm. Background technique [0002] With the development of electronic products towards light, thin, short and small, embedded passive device technology, which manufactures or embeds passive devices in the inner layer of the interconnection substrate to achieve high-density integration of components, has attracted extensive attention. This technology can effectively reduce the area of ​​the substrate, increase the wiring density and reduce the production cost. The shortening of the signal transmission path enables the embedded device to maintain signal integrity and reduce electromagnetic interference in the high-frequency and high-speed field. However, the improvement of component integration increases the power consumption per unit volume and the heat generation in the substrate a...

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Problems solved by technology

However, due to the unique premature convergence phenomenon of the genetic algorithm, the population diversity decreases sharply in the early evolutionary period, and the population lacks effective alleles, so the high-order competition pattern is no longer generated under the action of genetic operators[4]

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