DocumentCode :
2006036
Title :
Vendor selection using genetic algorithm
Author :
Sharmeen, S. ; Ali, M.A. ; Ripon, Shamim ; Kabir, Md Humayun ; Shil, N.C.
Author_Institution :
Dept. of Comput. Sci. & Eng., East West Univ., Dhaka, Bangladesh
fYear :
2012
fDate :
20-24 Nov. 2012
Firstpage :
1877
Lastpage :
1881
Abstract :
Selecting the right vendor is a complex business decision due to a huge number of competing vendors with a large number of complex criteria. The organization will suffer in the long run if vendors are not chosen wisely. Under multi criteria decision making, an algorithm, named VSFI, based on fuzzy clustering was proposed to select the most optimal vendors. VSFI highly depends on the randomized initial values of fuzzy clustering algorithm. This may sometime select wrong vendor. Addressing this problem, this paper proposes a genetic algorithm based solution using a fitness function. This solution finds the best vendor successfully. It can also suggest the competing vendors to improve themselves in some criteria so that they can increase their chance of winning in the selection process.
Keywords :
decision making; fuzzy set theory; genetic algorithms; operations research; pattern clustering; VSFI algorithm; business decision; complex criteria; fitness function; fuzzy clustering algorithm; genetic algorithm; most optimal vendor selection; multicriteria decision making; randomized initial values; AHP; Fuzzy clustering; genetic algorithm and vendor selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-2742-8
Type :
conf
DOI :
10.1109/SCIS-ISIS.2012.6505246
Filename :
6505246
Link To Document :
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