Robust Agricultural Supply Chain Management with Various Random and Fuzzy Parameters

Takashi Hasuike, Tomoko Kashima, Shimpei Matsumoto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper proposes a robust model of multiperiod agricultural supply chain to consider both maximizing the total profit and minimizing the environmental load with random and fuzzy parameters. Our proposed model is formulated as a fuzzy and stochastic, multiobjective and multiperiod programming problem, and hence, it is hard to solve the formulated problem directly without setting a specific random distribution and a specific membership function. Therefore, a distribution-free approach based on sample mean and variance derived from received data, which does not assume any specific random distributions and membership functions, is introduced to apply our proposed model to various uncertain conditions. In addition, deterministic equivalent transformations are also introduced to obtain the optimal solution efficiently using the scenario-based approach.

    Original languageEnglish
    Title of host publicationProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages11-16
    Number of pages6
    ISBN (Electronic)9781538606216
    DOIs
    Publication statusPublished - 2017 Nov 15
    Event6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 - Hamamatsu, Shizuoka, Japan
    Duration: 2017 Jul 9 → …

    Other

    Other6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
    CountryJapan
    CityHamamatsu, Shizuoka
    Period17/7/9 → …

    Keywords

    • Agricultural supply chain management
    • Distribution-free approach
    • Fuzziness
    • Mathematical programming problem
    • Randomness

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Computer Science Applications
    • Information Systems
    • Information Systems and Management

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  • Cite this

    Hasuike, T., Kashima, T., & Matsumoto, S. (2017). Robust Agricultural Supply Chain Management with Various Random and Fuzzy Parameters. In Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 (pp. 11-16). [8113204] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IIAI-AAI.2017.88