DocumentCode :
1651030
Title :
Application of Improved Genetic Algorithm in Virtual Enterprise Partnership Selection
Author :
Jianghong, Han ; Meifang, Wang ; Xuesen, Ma ; Yuefei, Wang
Author_Institution :
Hefei Univ. of Technol., Hefei
fYear :
2007
Firstpage :
771
Lastpage :
775
Abstract :
Partner selection is a key problem of organizing a virtual enterprise. A multi-objective optimization model, which analyzes these candidate enterprises quantitatively is proposed and accomplished by an improved genetic algorithm. This algorithm sorts several single object fitness using quick-sorting algorithm and selects based on total fitness, crossovers and mutates using the self-adaptive probability, and finds the global optimal solution at last. Through comparison with standard GA and the improved self-adaptive GA, simulation example testifies the latter efficiency.
Keywords :
commerce; genetic algorithms; probability; sorting; virtual enterprises; genetic algorithm; multiobjective optimization model; object fitness; quick-sorting algorithm; selfadaptive probability; virtual enterprise partnership selection; Algorithm design and analysis; Application software; Computer science education; Control engineering education; Educational technology; Genetic algorithms; Industrial control; Organizing; Safety; Virtual enterprises; Genetic Algorithm (GA); Multi-Objective Optimization; Partner Selection; Virtual Enterprise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
Type :
conf
DOI :
10.1109/CHICC.2006.4347326
Filename :
4347326
Link To Document :
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