A combined transportation model for the fruit and vegetable supply chain network
الموضوعات :Javid Ghahremani-Nahr 1 , Seyyed Esmaeil Najafi 2 , Hamed Nozari 3
1 - Faculty member of ACECR, Tabriz, Iran
2 - Department of Industrial Engineering, Islamic Azad University, Science and Research Branch
3 - Faculty of Industrial Engineering, Iran University of Science and Technology
الکلمات المفتاحية: Product perishability, Fruit and Vegetable Supply Chain, Combined Transportation, Robust Fuzzy Stochastic Optimization Method,
ملخص المقالة :
In this research, the problem of combined transportation in the supply chain of fruits and vegetables under uncertainty has been modeled. The designed model includes 4 levels consisting of cultivation, packaging, distribution and customer centers that aim to meet customer demand for perishable products (fruits and vegetables) under conditions of uncertainty in different scenarios. The presence of multiple vehicles in the supply chain network at different costs has led to the model showing the most suitable combined transport based on the results of the model solution by CPLEX method. Data, and as the probability increases or decreases, the amount of transfer time decreases. The result of changes in uncertainty rates also shows that with increasing uncertainty rates, the amount of demand increases and as a result, more transportation options are used for transportation. This has led to an increase in product transfer time. In the most important sensitivity analysis regarding the time of corruption, it was found that with the increase of corruption time, due to the possibility of storing perishable products and avoiding unwanted transportation, the possibility of using high speed vehicles has been provided and transfer time has decreased. Also, by analyzing the objective function and computational time in larger sizes with SCA and GA algorithms, it was observed that there is no significant difference between the mean indices and the SCA algorithm has a higher efficiency than the GA algorithm in obtaining the value of the objective function in acceptable time.
Aghaei Fishani, B., Mahmoodirad, A., Niroomand, S., & Fallah, M. (2022). Developing a Fuzzy Green Supply Chain Management Problem Considering Location Allocation Routing Problem: Hybrid Meta-Heuristic Approach. Journal of Optimization in Industrial Engineering, 15(1), 161-174.
Amiri, S. A. H. S., Zahedi, A., Kazemi, M., Soroor, J., & Hajiaghaei-Keshteli, M. (2020). Determination of the optimal sales level of perishable goods in a two-echelon supply chain network. Computers & Industrial Engineering, 139, 106156.
Arasteh, A. (2022). Optimizing inventory management costs in supply chains by determining safety stock placement. Journal of Optimization in Industrial Engineering, 15(1), 1-15.
Biuki, M., Kazemi, A., & Alinezhad, A. (2020). An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. Journal of Cleaner Production, 260, 120842.
Chouhan, V. K., Khan, S. H., & Hajiaghaei-Keshteli, M. (2021). Metaheuristic approaches to design and address multi-echelon sugarcane closed-loop supply chain network. Soft Computing, 25(16), 11377-11404.
Etemadnia, H., Goetz, S. J., Canning, P., & Tavallali, M. S. (2015). Optimal wholesale facilities location within the fruit and vegetables supply chain with bimodal transportation options: An LP-MIP heuristic approach. European Journal of Operational Research, 244(2), 648-661.
Fakhrzad, M. B., & Goodarzian, F. (2021). A new multi-objective mathematical model for a Citrus supply chain network design: Metaheuristic algorithms. Journal of Optimization in Industrial Engineering, 14(2), 127-144.
Gardas, B. B., Raut, R. D., & Narkhede, B. (2017). Modeling causal factors of post-harvesting losses in vegetable and fruit supply chain: An Indian perspective. Renewable and sustainable energy reviews, 80, 1355-1371.
Ghahremani Nahr, J., Pasandideh, S. H. R., & Niaki, S. T. A. (2020). A robust optimization approach for multi-objective, multi-product, multi-period, closed-loop green supply chain network designs under uncertainty and discount. Journal of industrial and production engineering, 37(1), 1-22.
Ghahremani-Nahr, J., Nozari, H., & Sadeghi, M. E. (2021). Investment modeling to study the performance of dynamic networks of insurance companies in Iran. Modern Research in Performance Evaluation.
Hosseini-Motlagh, S. M., Samani, M. R. G., & Abbasi Saadi, F. (2021). Strategic optimization of wheat supply chain network under uncertainty: a real case study. Operational research, 21(3), 1487-1527.
Hua, J., Gu, S., & Zhang, L. (2018). Optimal design of node distribution in maritime logistics network of fruit and vegetable supply chain. Journal of Coastal Research, (83 (10083)), 814-818.
Jabarzadeh, Y., Yamchi, H. R., Kumar, V., & Ghaffarinasab, N. (2020). A multi-objective mixed-integer linear model for sustainable fruit closed-loop supply chain network. Management of Environmental Quality: An International Journal.
Jiao, X., Xu, W., & Duan, L. (2021). Study on Cold Chain Transportation Model of Fruit and Vegetable Fresh-Keeping in Low-Temperature Cold Storage Environment. Discrete Dynamics in Nature and Society, 2021.
Jouzdani, J., & Govindan, K. (2021). On the sustainable perishable food supply chain network design: A dairy products case to achieve sustainable development goals. Journal of Cleaner Production, 278, 123060.
Khandelwal, C., Singhal, M., Gaurav, G., Dangayach, G. S., & Meena, M. L. (2021). Agriculture Supply Chain Management: A Review (2010–2020). Materials Today: Proceedings, 47, 3144-3153.
Liao, Y., Kaviyani-Charati, M., Hajiaghaei-Keshteli, M., & Diabat, A. (2020). Designing a closed-loop supply chain network for citrus fruits crates considering environmental and economic issues. Journal of Manufacturing Systems, 55, 199-220.
Mirjalili, S. (2016). SCA: a sine cosine algorithm for solving optimization problems. Knowledge-based systems, 96, 120-133.
Mousavi, S. M., Alikar, N., Niaki, S. T. A., & Bahreininejad, A. (2015). Optimizing a location allocation-inventory problem in a two-echelon supply chain network: A modified fruit fly optimization algorithm. Computers & Industrial Engineering, 87, 543-560.
Nahr, J. G., Nozari, H., & Sadeghi, M. E. (2021). Green supply chain based on artificial intelligence of things (AIoT). International Journal of Innovation in Management, Economics and Social Sciences, 1(2), 56-63.
Nozari, H., Ghahremani-Nahr, J., & Szmelter-Jarosz, A. (2022). A multi-stage stochastic inventory management model for transport companies including several different transport modes. International Journal of Management Science and Engineering Management, 1-11.
Nozari, H., Ghahremani-Nahr, J., Fallah, M., & Szmelter-Jarosz, A. (2022). Assessment of cyber risks in an IoT-based supply chain using a fuzzy decision-making method. International Journal of Innovation in Management, Economics and Social Sciences, 2(1).
Nozari, H., Szmelter-Jarosz, A., & Ghahremani-Nahr, J. (2021). The Ideas of Sustainable and Green Marketing Based on the Internet of Everything—The Case of the Dairy Industry. Future Internet, 13(10), 266.
Patidar, R., & Agrawal, S. (2020). Restructuring the Indian agro-fresh food supply chain network: a mathematical model formulation. Clean Technologies and Environmental Policy, 22(10), 2053-2077.
Raut, R. D., Gardas, B. B., Narwane, V. S., & Narkhede, B. E. (2019). Improvement in the food losses in fruits and vegetable supply chain-a perspective of cold third-party logistics approach. Operations Research Perspectives, 6, 100117.
Rizou, M., Galanakis, I. M., Aldawoud, T. M., & Galanakis, C. M. (2020). Safety of foods, food supply chain and environment within the COVID-19 pandemic. Trends in food science & technology, 102, 293-299.
Rizvi, S. A. A., Asim, M., & Manzoor, S. (2020). Issues, Challenges, and Scope of Supply Chain Management in Fruits and Vegetables in Pakistan. Int. European Extended Enablement in Sci., Engi. Magt, 8(1), 20-30.
Ronaghi, M. H. (2021). A blockchain maturity model in agricultural supply chain. Information Processing in Agriculture, 8(3), 398-408.
Rzaei, M., Dabbagh, R., & Baba Zade, R. (2021). Presenting a supply chain model using a mathematical programming method to optimize product distribution plan in the fruit industry. Iranian Journal of Agricultural Economics and Development Research.
Sahebjamnia, N., Goodarzian, F., & Hajiaghaei-Keshteli, M. (2020). Optimization of multi-period three-echelon citrus supply chain problem. Journal of Optimization in Industrial Engineering, 13(1), 39-53.
Salehi-Amiri, A., Zahedi, A., Akbapour, N., & Hajiaghaei-Keshteli, M. (2021). Designing a sustainable closed-loop supply chain network for walnut industry. Renewable and Sustainable Energy Reviews, 141, 110821.
Sathapatyanon, J., & Kuwornu, J. K. (2019). Assessment of the role of cooperative networks in the fruit supply chain in Thailand. International Journal of Value Chain Management, 10(1), 53-85.
Szmelter-Jarosz, A., Ghahremani-Nahr, J., & Nozari, H. (2021). A neutrosophic fuzzy optimisation model for optimal sustainable closed-loop supply chain network during COVID-19. Journal of Risk and Financial Management, 14(11), 519.
Tama, I. P., Akbar, Z., & Eunike, A. (2018, April). Implementation of system dynamic simulation method to optimize profit in supply chain network of vegetable product. In IOP Conference Series: Materials Science and Engineering (Vol. 337, No. 1, p. 012014). IOP Publishing.
Trivedi, A., Sohal, A., Joshi, S., & Sharma, M. (2021). A two-stage optimization model for tactical planning in fresh fruit supply chains: A case study of Kullu, India. International Journal of Supply and Operations Management, 8(1), 18-28.
Wang, A., Wang, Y., & Chen, Q. (2021). Analyzing Network Model for Organic Vegetable Distribution: A Case Study of Zhengzhou City. Mobile Information Systems, 2021.
Widi, A., Sari, E. D., & Jahroh, S. (2021, February). The Change of Fruit Supply Chain in Response to Covid-19 Pandemic in West Java, Indonesia (Case Study of Anto Wijaya Fruit). In Journal of Physics: Conference Series (Vol. 1764, No. 1, p. 012036). IOP Publishing.
Yin, H. L., & Wang, Y. M. (2017, July). An effective method for vegetable supply chain quality management. In 2017 36th Chinese Control Conference (CCC) (pp. 7507-7510). IEEE.
