An extensible genetic algorithm framework for problem solving in a common environment

被引：8

作者：

Chuang, AS ^{[1
]}

Wu, FL

机构：

[1] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA

[2] Univ Hong Kong, Ctr Elect Energy Syst, Hong Kong, Hong Kong, Peoples R China

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2000年 / 15卷 / 01期

关键词：

genetic algorithms; graphical user interfaces; object-oriented programming; optimization methods;

D O I：

10.1109/59.852132

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We describe an object-oriented framework for solving mathematical programs using genetic algorithms (GA's). The advantages of this framework are its extensibility, modular design, and accessibility to existing programming code. The framework also incorporates a graphical user's interface that may be used to build new GA's as well as run GA simulations. Two power system problems are solved by implementing genetic algorithms using the said framework. The first is a continuous optimization problem and the second an integer programming problem. We illustrate the flexibility of the framework as well as its other features on our test problems.

引用

页码：269 / 275

页数：7

共 27 条

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