Title :
Particle Clonal Genetic Algorithm Using Sequence Coding for Solving Distribution Network Reconfiguration
Author :
Yemei Qin ; Ji Wang ; Weihua Gui
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha
Abstract :
To handle massive binary-coding infeasible solutions in distribution network reconfiguration, a sequence coding is presented. A loop is a gene and the switch sequence in the loop is the gene value. To resolve mutation probability and slow later-period convergence in clonal genetic algorithm(CGA), particle clonal genetic algorithm(PCGA) is proposed. It builds particle swarm algorithm (PSO) mutation operator, and makes up premature convergence of PSO and blindness of CGA. It ensures evolution direction and range based on historical records and swarm records. Global optimal solution is found with fewer generations and shorter searching time. IEEE69 example shows that the method can save calculation time and promote search efficiency obviously.
Keywords :
binary codes; convergence; distribution networks; genetic algorithms; mathematical operators; particle swarm optimisation; probability; search problems; binary coding; convergence; distribution network reconfiguration; global optimal solution; mutation operator; mutation probability; particle clonal genetic algorithm; particle swarm optimisation algorithm; search problem; sequence coding; Biological cells; Blindness; Computer networks; Distributed computing; Educational institutions; Genetic algorithms; Genetic mutations; Information science; Particle swarm optimization; Switches; PCGA; distribution network reconfiguration; infeasible solution; sequence coding;
Conference_Titel :
Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3398-8
Electronic_ISBN :
978-0-7695-3398-8
DOI :
10.1109/ICYCS.2008.326