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

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2 Author(s)
Chuang, A.S. ; Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA ; Wu, F.

The authors describe an object-oriented framework for solving mathematical power system programs using genetic algorithms (GAs). The advantages of this framework are its extensibility, modular design and accessibility to existing programming code. The framework also incorporates a graphical user interface that may be used to build new GAs 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. The authors illustrate the flexibility of the framework as well as its other features on their test problems

Published in:

Power Systems, IEEE Transactions on  (Volume:15 ,  Issue: 1 )

Date of Publication:

Feb 2000

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