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Production Planning Optimization in a Two-Echelon Multi-Product Supply Chain with Discrete Delivery and Storage at Manufacturer’s Warehouse

Author

Listed:
  • Maedeh Tajik

    (Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Seyed Mohammad Hajimolana

    (Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Mohammad Daneshvar Kakhki

    (Haworth College of Business, Western Michigan University, Kalamazoo, MI 49008, USA
    College of Business, California State University, Long Beach, CA 90840, USA)

Abstract

In today’s competitive world, customers expect their demands to be met at the shortest possible time, while manufacturers aspire to deliver the orders within a convenient time and at a minimum cost. Thus, manufacturers are compelled to seek ways of lowering the costs of their services in order to satisfy customers and survive the competition in their respective industries. This research paper investigates a multi-product problem in a two-echelon supply chain consisting of a single manufacturer and several retailers. The main objective of this research is to develop and present a multi-product optimization model in which retailers receive their orders through discrete delivery and surplus manufactured goods are stored in the manufacturer’s warehouse. The objective function of the mathematical model in the economic dimension includes the minimization of the total supply chain costs and the maximization of profit. The retailers in this model place new orders when their inventory level drops to zero, and the manufacturer responds to the retailers’ orders at the same time as it begins processing each product. After delivering the last set of orders, the manufacturer stores surplus items in its warehouse in case the retailers place new orders. This optimization problem is modeled using mixed integer nonlinear programming, while numerical scenarios are coded using the MATLAB software which helps estimate the total cost within a short time. Finally, a sensitivity analysis is performed to determine the effects of a number of factors on the total cost, including problem parameters, demand and production rates, the production quantity, and the number of times the manufacturing machines are operated at each production cycle.

Suggested Citation

  • Maedeh Tajik & Seyed Mohammad Hajimolana & Mohammad Daneshvar Kakhki, 2024. "Production Planning Optimization in a Two-Echelon Multi-Product Supply Chain with Discrete Delivery and Storage at Manufacturer’s Warehouse," Mathematics, MDPI, vol. 12(13), pages 1-19, June.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:1986-:d:1423645
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    References listed on IDEAS

    as
    1. 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.
    2. Amir Hossein Nobil & Seyed TaghiAkhavanNiaki & Erfan Nobil, 2017. "An Effective and Simple Algorithm to Solve the Discrete Multi-Product Economic Production Quantity Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(3), pages 251-261.
    3. Berghman, Lotte & Kergosien, Yannick & Billaut, Jean-Charles, 2023. "A review on integrated scheduling and outbound vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 1-23.
    Full references (including those not matched with items on IDEAS)

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