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Vendor selection using genetic algorithm

Authors: Shaila Sharmeen; Nikhil Chandra Shil; M. Ameer Ali; Md. Humayun Kabir; Shamim Ripon;

Vendor selection using genetic algorithm

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.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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