Fuzzy multi-criteria selection among transportation companies with fuzzy linguistic preference relations
Expert Systems with ApplicationsPublished 11 March 2011
Tien-Chin Wang, Ying-Hsiu Chen
Citations23
SJR quartileQ1
SJR score1.85
SNIP2.55
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TL;DR
Analytical results indicate that the fuzzy LinPreRa is more suitable and efficient for providing rankings of transportation companies for making decisions, and assigning linguistic variables to judgments is simpler and more intuitive than fixed value judgments.
Abstract
Selecting an appropriate transportation company is an important decision for an effective supply chain. This study attempts to solve transportation company selection problems initially addressed by Kulak and Kahraman in 2005, by adopting two methods. Consistent fuzzy preference relations presented by Herrera-Viedma et al. and fuzzy linguistic preference relations (fuzzy LinPreRa) developed by Wang and Chen in 2008. Analytical results indicate that both methods produce a consistent decision results from only n − 1 pairwise comparisons. However, assigning linguistic variables to judgments is simpler and more intuitive than fixed value judgments. Therefore, the fuzzy LinPreRa is more suitable and efficient for providing rankings of transportation companies for making decisions.
Keywords
Decision SciencesMathematicsEngineering
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