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Volume 14, Issue 3 (Autumn 2024)
Disaster Prev. Manag. Know. 2024, 14(3): 292-309 |
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Kheyrati L, Darvish Motevalli M H. Presenting a Mathematical Model for Optimizing the Cold Food Supply Chain During Disasters. Disaster Prev. Manag. Know. 2024; 14 (3) :292-309
URL: http://dpmk.ir/article-1-691-en.html
URL: http://dpmk.ir/article-1-691-en.html
1- Department of Information Technology Management, Kish International Branch, Islamic Azad University, Kish, Iran.
2- Department of Industrial Management, Faculty of Management, West Tehran Branch, Islamic Azad University, Tehran, Iran.
2- Department of Industrial Management, Faculty of Management, West Tehran Branch, Islamic Azad University, Tehran, Iran.
Abstract: (3845 Views)
Background and objective One of the most important goals of the crisis management headquarters is the proper preparation and distribution of food to the affected people during a disaster. Due to the limitations related to shelf life and storage of perishable food products, operational costs, and transportation, their distribution is challenging. In this study, we aim to develop a mathematical model using integer linear programming for the optimization of cold food supply chain during disasters.
Method This study uses an operational research approach. A two-objective mixed integer linear programming model was designed for a cold, stable and multi-level supply chain in the food industry in the conditions of uncertainty and crisis. In this programming model, the economic order quantity (EOQ) performance optimization method was used to determine the optimal order point. The presented model was solved based on the real data obtained from the crisis management headquarters in Iran and implemented as a pilot for 16 supply centers, 5 distribution channels, and 35 crisis management headquarters with two LP-metric and augmented epsilon constraint (AEC) methods.
Results The findings of testing research hypotheses using one-way analysis of variance showed that the use of mathematical models had a positive and significant effect on the optimization of the cold food supply chain during disasters. In this regard, there was no significant difference between LP-metric and AEC methods (P>0.05). Also, the use of mathematical models had a positive and significant effect on improving the quality of food industry. Optimizing the supply chain by the mathematical model has a positive and significant effect on the performance of food industries. The optimal order point in the chain model had a EOQ of 3436 units.
Conclusion By using the presented mathematical model, it is possible to optimize the management process of the cold food supply chain during disasters. It has a higher performance compared to traditional approaches. It is expected that by using the presented mathematical model, relief operations and food distribution during disasters can be facilitated and optimized.
Method This study uses an operational research approach. A two-objective mixed integer linear programming model was designed for a cold, stable and multi-level supply chain in the food industry in the conditions of uncertainty and crisis. In this programming model, the economic order quantity (EOQ) performance optimization method was used to determine the optimal order point. The presented model was solved based on the real data obtained from the crisis management headquarters in Iran and implemented as a pilot for 16 supply centers, 5 distribution channels, and 35 crisis management headquarters with two LP-metric and augmented epsilon constraint (AEC) methods.
Results The findings of testing research hypotheses using one-way analysis of variance showed that the use of mathematical models had a positive and significant effect on the optimization of the cold food supply chain during disasters. In this regard, there was no significant difference between LP-metric and AEC methods (P>0.05). Also, the use of mathematical models had a positive and significant effect on improving the quality of food industry. Optimizing the supply chain by the mathematical model has a positive and significant effect on the performance of food industries. The optimal order point in the chain model had a EOQ of 3436 units.
Conclusion By using the presented mathematical model, it is possible to optimize the management process of the cold food supply chain during disasters. It has a higher performance compared to traditional approaches. It is expected that by using the presented mathematical model, relief operations and food distribution during disasters can be facilitated and optimized.
Type of Study: Research |
Subject:
Special
Received: 2024/06/12 | Accepted: 2024/08/20 | ePublished: 2024/10/1
Received: 2024/06/12 | Accepted: 2024/08/20 | ePublished: 2024/10/1
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