Abstract
In many real-world multiple criteria group decision-making process, people cannot provide accurate preference information over a set of alternatives because of the increasingly complex environment. Fashion sales forecasting can be taken as a multi-criteria group decision-making problem given that people need to consider product life cycle, year-on-year growth rate, seasonal factor, industry factor, and consumer factor comprehensively when they forecast the fashion scales. In this paper, we developed a fuzzy linguistic model for fashion sales forecasting. Approaches such as hesitant fuzzy linguistic preference relation and ordinal consensus measure are used in our paper. Decision-makers compare alternatives over each criterion and the ranking of alternatives can be derived. Based on the ranking provided by the decision-makers, we introduce the ordinal consensus of the group. Then, a consensus reaching process is given to raise the degree of consensus.
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Acknowledgements
The work was supported by the National Natural Science Foundation of China (71501135, 71771156), the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23), the 2018 Key Project of the Key Research Institute of Humanities and Social Sciences in Sichuan Province (No. LYC18-02, No. DSWL18-2), and the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23).
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Tang, M., Liao, H. (2019). Multiple Criteria Group Decision-Making Based on Hesitant Fuzzy Linguistic Consensus Model for Fashion Sales Forecasting. In: Wong, W. (eds) Artificial Intelligence on Fashion and Textiles. AITA 2018. Advances in Intelligent Systems and Computing, vol 849. Springer, Cham. https://doi.org/10.1007/978-3-319-99695-0_40
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DOI: https://doi.org/10.1007/978-3-319-99695-0_40
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