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Multi Objective and Multi-Product Perishable Supply Chain with Vendor-Managed Inventory and IoT-Related Technologies

Author

Listed:
  • Tahereh Mohammadi

    (Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran
    Ph.D. student.)

  • Seyed Mojtaba Sajadi

    (Operations and Information Management Department, Aston Business School, Aston University, Birmingham B4 7ET, UK)

  • Seyed Esmaeil Najafi

    (Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Mohammadreza Taghizadeh-Yazdi

    (Faculty of Management, University of Tehran, Tehran 1417466191, Iran)

Abstract

With the emergence of the fourth industrial revolution, the use of intelligent technologies in supply chains is becoming increasingly common. The aim of this research is to propose an optimal design for an intelligent supply chain of multiple perishable products under a vendor-managed inventory management policy aided by IoT-related technologies to address the challenges associated with traditional supply chains. Various levels of the intelligent supply chain employ technologies such as Wireless Sensor Networks (WSNs), Radio Frequency Identification (RFID), and Blockchain. In this paper, we develop a bi-objective nonlinear integer mathematical programming model for designing a four-level supply chain consisting of suppliers, manufacturers, retailers, and customers. The model determines the optimal network nodes, production level, product distribution and sales, and optimal choice of technology for each level. The objective functions are total cost and delivery times. The GAMS 24.2.1 optimization software is employed to solve the mathematical model in small dimensions. Considering the NP-Hard nature of the problem, the Grey Wolf Optimizer (GWO) algorithm is employed, and its performance is compared with the Multi-Objective Whale Optimization Algorithm (MOWOA) and NSGA-III. The results indicate that the adoption of these technologies in the supply chain can reduce delivery times and total supply chain costs.

Suggested Citation

  • Tahereh Mohammadi & Seyed Mojtaba Sajadi & Seyed Esmaeil Najafi & Mohammadreza Taghizadeh-Yazdi, 2024. "Multi Objective and Multi-Product Perishable Supply Chain with Vendor-Managed Inventory and IoT-Related Technologies," Mathematics, MDPI, vol. 12(5), pages 1-30, February.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:679-:d:1346058
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    References listed on IDEAS

    as
    1. Lee, In & Lee, Kyoochun, 2015. "The Internet of Things (IoT): Applications, investments, and challenges for enterprises," Business Horizons, Elsevier, vol. 58(4), pages 431-440.
    2. Y. P. Tsang & C. H. Wu & H. Y. Lam & K. L. Choy & G. T. S. Ho, 2021. "Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1534-1556, March.
    3. C.K.M. Lee & Yaqiong Lv & K.K.H. Ng & William Ho & K.L. Choy, 2018. "Design and application of Internet of things-based warehouse management system for smart logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2753-2768, April.
    4. YU, Jie & Subramanian, Nachiappan & Ning, Kun & Edwards, David, 2015. "Product delivery service provider selection and customer satisfaction in the era of internet of things: A Chinese e-retailers’ perspective," International Journal of Production Economics, Elsevier, vol. 159(C), pages 104-116.
    5. Hiva Malekpour & Seyed Mojtaba Sajadi & Hashem Vahdani, 2016. "Using discrete-event simulation and the Taguchi method for optimising the production rate of network failure-prone manufacturing systems with perishable goods," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 23(4), pages 387-406.
    6. Chunguang Bai & Joseph Sarkis, 2020. "A supply chain transparency and sustainability technology appraisal model for blockchain technology," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2142-2162, April.
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