Genetic algorithm of Chu and Beasley for static and multistage transmission expansion planning

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Data

2006-01-01

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Ieee

Resumo

In this paper the genetic algorithm of Chu and Beasley (GACB) is applied to solve the static and multistage transmission expansion planning problem. The characteristics of the GACB, and some modifications that were done, to efficiently solve the problem described above are also presented. Results using some known systems show that the GACB is very efficient. To validate the GACB, we compare the results achieved using it with the results using other meta-heuristics like tabu-search, simulated annealing, extended genetic algorithm and hibrid algorithms.

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transmission expansion planning, genetic algorithm of Chu and Beasley, meta-heuristics, combinatorial optimization

Como citar

2006 Power Engineering Society General Meeting, Vols 1-9. New York: Ieee, p. 4276-+, 2006.