Providing a multi-objective sustainable distribution network of agricultural items considering uncertainty and time window using meta-heuristic algorithms

محورهای موضوعی : Design of Experiment

Abbas Toloie Ashlaghi ¹ (Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.)
Amir Daneshvar ² (Department of Information Technology Management, Electronic Branch, Islamic Azad University, Tehran, Iran)
Adel Pourghader Chobar ³ (Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran)
Fariba Salahi ⁴ (Department of Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran)

تاریخ دریافت : 1402/10/16 تاریخ پذیرش : 1403/03/26 تاریخ انتشار : 1403/04/10

کلید واژه: stable network, agricultural items, uncertainty, meta-heuristic algorithm, Jimenez fuzzy, time window,

چکیده مقاله :

In this article, a sustainable network of distribution of agricultural items with suppliers, distribution centers, and retailers is considered. The main purpose of presenting the mathematical model in this article is to determine the optimal number and location of suppliers, assigning suppliers to distribution centers and optimal routing for the distribution of agricultural items to retailers in a predefined time window. Also, determining the optimal amount of inventory and the reorder point in retailers and distribution centers is another problem decision. To model the problem, some parameters of the model were considered non-deterministic and were controlled by the probabilistic fuzzy method. The results of solving numerical examples in different sizes showed that with the increase of the total costs of the distribution network of agricultural items, the amount of greenhouse gas emissions decreases, and the employment rate increases. Also, with the increase of the uncertainty rate, due to the increase of the real demand and the change in the optimal amount of production, distribution, storage and reorder point, the values of all the objective functions also increase. It was also observed by solving different numerical examples with NSGA II and MOGWO algorithms, these algorithms have been able to solve the problem in a much shorter period than the epsilon constraint method, and comparison indicators such as NPF, MSI, SM, and computing time show These algorithms have a high efficiency in solving numerical examples of the problem of the distribution network of agricultural items.

چکیده انگلیسی:

In this article, a sustainable network of distribution of agricultural items with suppliers, distribution centers, and retailers is considered. The main purpose of presenting the mathematical model in this article is to determine the optimal number and location of suppliers, assigning suppliers to distribution centers and optimal routing for the distribution of agricultural items to retailers in a predefined time window. Also, determining the optimal amount of inventory and the reorder point in retailers and distribution centers is another problem decision. To model the problem, some parameters of the model were considered non-deterministic and were controlled by the probabilistic fuzzy method. The results of solving numerical examples in different sizes showed that with the increase of the total costs of the distribution network of agricultural items, the amount of greenhouse gas emissions decreases, and the employment rate increases. Also, with the increase of the uncertainty rate, due to the increase of the real demand and the change in the optimal amount of production, distribution, storage and reorder point, the values of all the objective functions also increase. It was also observed by solving different numerical examples with NSGA II and MOGWO algorithms, these algorithms have been able to solve the problem in a much shorter period than the epsilon constraint method, and comparison indicators such as NPF, MSI, SM, and computing time show These algorithms have a high efficiency in solving numerical examples of the problem of the distribution network of agricultural items.

منابع و مأخذ:

Ada, N. (2022). Sustainable Supplier Selection in Agri-Food Supply Chain Management. International Journal of Mathematical, Engineering and Management Sciences, 7(1), 115.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Esteso, A., Alemany, M. M. E., & Ortiz, Á. (2021). Impact of product perishability on agri-food supply chains design. Applied Mathematical Modelling, 96, 20-38.
Chobar, A. P., Adibi, M. A., & Kazemi, A. (2022). Multi-objective hub-spoke network design of perishable tourism products using combination machine learning and meta-heuristic algorithms. Environment, Development and Sustainability, 1-28.
Ghasemkhani, A., Tavakkoli-Moghaddam, R., Rahimi, Y., Shahnejat-Bushehri, S., & Tavakkoli-Moghaddam, H. (2022). Integrated production-inventory-routing problem for multi-perishable products under uncertainty by meta-heuristic algorithms. International Journal of Production Research, 60(9), 2766-2786.
Iraj, M., Chobar, A. P., Peivandizadeh, A., & Abolghasemian, M. (2024). Presenting a two-echelon multi-objective supply chain model considering the expiration date of products and solving it by applying MODM. Sustainable Manufacturing and Service Economics, 3, 100022.
Ghezavati, V. R., Hooshyar, S., & Tavakkoli-Moghaddam, R. (2017). A Benders’ decomposition algorithm for optimizing distribution of perishable products considering postharvest biological behavior in agri-food supply chain: a case study of tomato. Central European Journal of Operations Research, 25(1), 29-54.
Giallanza, A., & Puma, G. L. (2020). Fuzzy green vehicle routing problem for designing a three echelons supply chain. Journal of Cleaner Production, 259, 120774.
Gruler, A., Panadero, J., de Armas, J., Pérez, J. A. M., & Juan, A. A. (2018). Combining variable neighborhood search with simulation for the inventory routing problem with stochastic demands and stock-outs. Computers & Industrial Engineering, 123, 278-288.
Gupta, M., Kaur, H., & Singh, S. P. (2021). Multi-echelon agri-food supply chain network design integrating operational and strategic objectives: a case of public distribution system in India. Annals of Operations Research, 1-58.
Harahap, A. Z. M. K., & Rahim, M. K. I. A. (2022). A Single Period Deterministic Inventory Routing Model for Solving Problems in the Agriculture Industry. Journal of Applied Science and Engineering, 25(6), 945-950.
Imran, M., Habib, M. S., Hussain, A., Ahmed, N., & Al-Ahmari, A. M. (2020). Inventory routing problem in supply chain of perishable products under cost uncertainty. Mathematics, 8(3), 382.
Jiménez, M., Arenas, M., Bilbao, A., & Rodrı, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European journal of operational research, 177(3), 1599-1609.
Kresnanto, N. C., Putri, W. H., Lantarsih, R., & Harjiyatni, F. R. (2021, February). Challenges in transportation policy: speeding up a sustainable agri-food supply chain. In IOP Conference Series: Earth and Environmental Science (Vol. 662, No. 1, p. 012006). IOP Publishing.
Li, D., Cao, Q., Zuo, M., & Xu, F. (2020). Optimization of green fresh food logistics with heterogeneous fleet vehicle route problem by improved genetic algorithm. Sustainability, 12(5), 1946.
Li, Y., Chu, F., Chu, C., Zhou, W., & Zhu, Z. (2016, November). Integrated production inventory routing planning with time windows for perishable food. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) (pp. 2651-2656). IEEE.
Mahjoob, M., Fazeli, S. S., Milanlouei, S., Tavassoli, L. S., & Mirmozaffari, M. (2022). A modified adaptive genetic algorithm for multi-product multi-period inventory routing problem. Sustainable Operations and Computers, 3, 1-9.

Mirjalili, S., Saremi, S., Mirjalili, S. M., & Coelho, L. D. S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, 47, 106-119.
Misni, F., Lee, L. S., & Seow, H. V. (2020). Hybrid harmony search-simulated annealing algorithm for location-inventory-routing problem in supply chain network design with defect and non-defect items. Applied Sciences, 10(18), 6625.
Onggo, B. S., Panadero, J., Corlu, C. G., & Juan, A. A. (2019). Agri-food supply chains with stochastic demands: A multi-period inventory routing problem with perishable products. Simulation Modelling Practice and Theory, 97, 101970.
Pratap, S., Jauhar, S. K., Paul, S. K., & Zhou, F. (2022). Stochastic optimization approach for green routing and planning in perishable food production. Journal of Cleaner Production, 333, 130063.
Mahdavimanshadi, M., Anaraki, M. G., Mowlai, M., & Ahmadirad, Z. (2024, May). A Multistage Stochastic Optimization Model for Resilient Pharmaceutical Supply Chain in COVID-19 Pandemic Based on Patient Group Priority. In 2024 Systems and Information Engineering Design Symposium (SIEDS) (pp. 382-387). IEEE.
Saragih, N. I., Bahagia, N., & Syabri, I. (2019). A heuristic method for location-inventory-routing problem in a three-echelon supply chain system. Computers & Industrial Engineering, 127, 875-886.
Shirzadi, S., Ghezavati, V., Tavakkoli-Moghaddam, R., & Ebrahimnejad, S. (2021). Optimizing a sustainable inventory-routing problem in tomato agri-chain considering postharvest biological behavior. Journal of Industrial Engineering International, 17(2), 45-60.
Shirzadi, S., Ghezavati, V., Tavakkoli-Moghaddam, R., & Ebrahimnejad, S. (2021). Developing a green and bipolar fuzzy inventory-routing model in agri-food reverse logistics with postharvest behavior. Environmental Science and Pollution Research, 28(30), 41071-41088.
Song, L., & Wu, Z. (2022). An integrated approach for optimizing location-inventory and location-inventory-routing problem for perishable products. International Journal of Transportation Science and Technology.
Soysal, M., Bloemhof-Ruwaard, J. M., Haijema, R., & van der Vorst, J. G. (2018). Modeling a green inventory routing problem for perishable products with horizontal collaboration. Computers & Operations Research, 89, 168-182.
Taşkıner, T., & Bilgen, B. (2021). Optimization models for harvest and production planning in agri-food supply chain: A systematic review. Logistics, 5(3), 52.
Tavana, M., Tohidi, H., Alimohammadi, M., & Lesansalmasi, R. (2021). A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty. Environmental Science and Pollution Research, 28(36), 50636-50648.
Tirkolaee, E. B., Dashtian, Z., Weber, G. W., Tomaskova, H., Soltani, M., & Mousavi, N. S. (2021). An integrated decision-making approach for green supplier selection in an agri-food supply chain: Threshold of robustness worthiness. Mathematics, 9(11), 1304.
Zarean Dowlat Abadi, J., Iraj, M., Bagheri, E., RabieiPakdeh, Z., & Dehghani Tafti, M. R. (2022). A Multiobjective Multiproduct Mathematical Modeling for Green Supply Chain considering Location‐Routing Decisions. Mathematical Problems in Engineering, 2022(1), 7009338.
Violi, A., Laganá, D., & Paradiso, R. (2020). The inventory routing problem under uncertainty with perishable products: an application in the agri-food supply chain. Soft Computing, 24(18), 13725-13740