• Media type: E-Book
  • Title: Flexible Demand Forecasting in Intelligent Food Supply Chain Management
  • Contributor: Ravisankar, Srimathi [Author]; Mahendran, Kanimozhi [Author]; Arulmurugan, Srilakshmi [Author]; Sumalatha, M.R [Author]
  • Published: [S.l.]: SSRN, 2022
  • Extent: 1 Online-Ressource (11 p)
  • Language: English
  • DOI: 10.2139/ssrn.4119151
  • Identifier:
  • Keywords: Demand Forecasting ; Supply chain Management ; Food Traceability ; Information sharing ; Food Supply chain ; Blockchain
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 25, 2022 erstellt
  • Description: In the Food industry, big data analytics techniques and concepts are being applied in inventory optimization which combines the past data with the predictive techniques and enhance the Supply chain management techniques. There are three modules being dealt in this paper dealing with Food Supply chain management namely Demand Forecasting, Food tracing system and Information sharing module for Suppliers, Warehouse and restaurants to communicate among themselves. This paper proposes a novel algorithm for Demand Forecasting module that combines an outlier detection technique followed by LightGBM Regressor which handles specified target and SARIMA Algorithm which handles seasonality in data This paper also proposes a Food Tracing System(Find my Food) which uses Nakamoto Consensus method for participants to agree in network which will address the issues of traditional data invisibility, data manipulation, and sensitive information exposure and the Information sharing module between the supply chain entities using database where they can share about food quality issues, share information about the stock and requirement details of the ingredients needed for preparing meals in restaurant and stay connected with the Supply Chain Entities. This way of having a Information sharing module in supply chain helps in information sharing and maintaining supply chain hassle free
  • Access State: Open Access