Characteristic determination for solid state devices with evolutionary computation: A case study

Ping Chu Hung*, Ying-Ping Chen, Hsiao-Wen Zan

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

In this paper, we develop a new optimization framework that consists of the extended compact genetic algorithm (ECGA) and split-on-demand (SoD), an adaptive discretization technique, to tackle the characteristic determination problem for solid state devices. As most decision variables of characteristic determination problems are real numbers due to the modeling of physical phenomena, and ECGA is designed for handling discrete-type problems, a specific mechanism to transform the variable types of the two ends is in order. In the proposed framework, ECGA is used as a back-end optimization engine, and SoD is adopted as the interface between the engine and the problem. Moreover, instead of one mathematical model with various parameters, characteristic determination is in fact a set of problems of which the mathematical formulations may be very different. Therefore, in this study, we employ the proposed framework on three study cases to demonstrate that the technique proposed in the domain of evolutionary computation can provide not only the high quality optimization results but also the flexibility to handle problems of different formulations.

原文English
主出版物標題Proceedings of GECCO 2007
主出版物子標題Genetic and Evolutionary Computation Conference
頁面2029-2036
頁數8
DOIs
出版狀態Published - 2007
事件9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, United Kingdom
持續時間: 7 7月 200711 7月 2007

出版系列

名字Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference

Conference

Conference9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
國家/地區United Kingdom
城市London
期間7/07/0711/07/07

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