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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.
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). | 0 | |
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. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |