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TitleOptimization decision model of vegetable stock and pricing based on TCN-Attention and genetic algorithm
Creator
Date Issued2023-10-13
Source PublicationACM International Conference Proceeding Series
Pages739-745
AbstractWith the expansion of operational scale of supermarkets in China, the vegetable market has grown considerably. The decision-making related to procurement costs and allocation quantities of vegetables has become a pivotal factor in determining the profitability of supermarkets. This paper analyzes the relationship between pricing and allocation faced by supermarkets in vegetable operations. Optimization algorithms are employed to determine replenishment and pricing strategies. Linear regression is utilized to model the historical data of various products, establishing the relationship between sale prices and sales volumes for 61 products. By integrating historical data on vegetable costs with time information based on the 24 solar terms, a cost prediction model is trained using TCN-Attention. The Topis evaluation model identifies the 32 most market-demanded products. A genetic algorithm is then used to search for the globally optimized vegetable product allocation-pricing decision.
Keywordbootstrap sampling genetic algorithm TCN-Attention time series encoding Topsis
DOI10.1145/3644523.3644657
URLView source
Language英语English
Scopus ID2-s2.0-85190375987
Citation statistics
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/11561
CollectionBeijing Normal-Hong Kong Baptist University
Corresponding AuthorXia,Linhan
Affiliation
Beijing Normal University,Hong Kong Baptist University United International College,Guangdong,Zhuhai,China
First Author AffilicationBeijing Normal-Hong Kong Baptist University
Corresponding Author AffilicationBeijing Normal-Hong Kong Baptist University
Recommended Citation
GB/T 7714
Xia,Linhan,Zhang,Jinyuan,Wen,Bohan. Optimization decision model of vegetable stock and pricing based on TCN-Attention and genetic algorithm[C], 2023: 739-745.
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