Genetic algorithm of chu and beasley for static and multistage transmission expansion planning
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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. © 2006 IEEE.
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Combinatorial optimization, Genetic algorithm of Chu and Beasley, Meta-heuristics, Transmission expansion planning, Genetic algorithms, Problem solving, Simulated annealing, Strategic planning, Electric power transmission
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Inglês
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2006 IEEE Power Engineering Society General Meeting, PES.
