Volume 22, Issue 3 (9-2025)                   jor 2025, 22(3): 141-159 | Back to browse issues page

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Nemati A, Mehravaran M. A Multi-Period, Multi-Season Mathematical Model for Resilient Distribution Network Planning (A Case Study of Automobile Part-Making Industry). jor 2025; 22 (3) :141-159
URL: http://jamlu.liau.ac.ir/article-1-2277-en.html
A Multi-Period, Multi-Season Mathematical Model for Resilient Distribution Network Planning (A Case Study of Automobile Part-Making Industry)
A. Nemati * , M. Mehravaran
Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol City, Mazandaran, Iran , r.nemati@nit.ac.ir
Abstract:   (25 Views)
Seasonal fluctuations in supply chain parameters are commonly caused by weather conditions variations, religious or national ceremonies, holidays, and periodic pricing strategies. As an example, the New Year holidays affect the demand for goods and services, such as food, water, hospitality, and transport. Hence, coordination of the supply chain items and operations, such as production, warehousing, purchasing, and transportation, according to seasonal demand, has been aimed at supply chain responsiveness and efficiency. Also, proposing price menus for raw materials by suppliers motivates supply chain decision-makers to redesign purchasing strategies according to seasonal fluctuations of supply. In addition, weather conditions and tourism seasons lead to seasonal fluctuations in the transportation system parameters, such as capacity, accessibility, price, and agility. Resilient supply chains are capable of tolerating disruptions and recovering in the short run. Considering additional capacities, such as production and warehousing, and providing surplus capacities in human resources and financial affairs are commonly used resiliency strategies in supply chain design and planning. 

 
Keywords: Seasonal Distribution Network Planning, Resilience, Seasonal Transportation, Seasonal Demand, Multi-Period Multi-Season Linear Mathematical Model, Automobile Part-Making Industry.
     
Type of Study: Research | Subject: Special
Received: 2025/03/16 | Accepted: 2025/07/28
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