DocumentCode :
2372662
Title :
Pseudo-parallel genetic algorithm in process mining
Author :
Xue, Gang ; Ye, Xiaohu ; Yang, Jinwu
Author_Institution :
Nat. Pilot Sch. of Software, Yunnan Univ., Kunming, China
fYear :
2012
fDate :
23-25 March 2012
Firstpage :
623
Lastpage :
626
Abstract :
Process mining is helpful for deploying new business processes as well as auditing, analyzing and improving the already enacted ones. An improved pseudo-parallel genetic algorithm is proposed with an asexual reproduction for avoiding crossover operators´ breach to nice gene patterns. The initial population is produced by greedy algorithm in order to enhance convergence velocity. Information exchange between subgroups employs island model in pseudo-parallel genetic algorithm. These measures are of great significance on reducing complexities and enhancing convergence velocity, as well as increasing global searching ability of the algorithm.
Keywords :
business data processing; computational complexity; genetic algorithms; greedy algorithms; parallel algorithms; search problems; business process; complexities; convergence velocity; gene pattern; global searching ability; greedy algorithm; information exchange; island model; process mining; pseudoparallel genetic algorithm; subgroup; Business; Convergence; Data mining; Educational institutions; Genetic algorithms; Genetics; Software engineering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2012 International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-1-4577-0343-0
Type :
conf
DOI :
10.1109/ICIST.2012.6221720
Filename :
6221720
Link To Document :
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