cris.boxmetadata.label.title
Genetic algorithm of chu and beasley for static and multistage transmission expansion planning
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.december 2006
cris.boxmetadata.label.accesslevel
metadata only access
cris.boxmetadata.label.resourcetype
conference paper
cris.boxmetadata.label.authors
De Silva I.J.
Rider M.J.
Romero R.
Murari C.A.
cris.boxmetadata.label.abstract
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.
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Genética, Herencia
cris.boxmetadata.label.subjects
cris.boxmetadata.label.scopusidentifier
2-s2.0-35348899544
cris.boxmetadata.label.isbn
1424404932
9781424404933
cris.boxmetadata.label.conference
2006 IEEE Power Engineering Society General Meeting, PES
peru-layout.shadow-copies
Directorio de Producción Científica
Scopus