Journal of Industrial and Systems Engineering

Journal of Industrial and Systems Engineering

Optimization of location-routing-inventory problem for perishable products with WOA and ALO algorithms

Document Type : Research Paper

Authors
Department of Management, Azad University, Dubai Branch, Dubai, United Arab Emirates
Abstract
This paper discusses the modeling of a location-routing-inventory problem for perishable products. The model presented in this paper includes a three-echelon supply chain of suppliers, distribution centers, and retailers. Supplier selection, assigning suppliers to distribution centers and retailers, vehicle routing and economic order quantity, lead time, and confidence inventory are the main decisions of the problem. These decisions are aimed at optimizing the total supply chain network costs. The nonlinear model presented in this article has been solved using two algorithms, WOA and ALO, in 12 sample problems. The results show that the solving speed of these algorithms and the high quality of the obtained answers are very high compared to the exact method. So, the maximum percentage of relative difference between the obtained results is less than 1%. The sensitivity analysis on the perishability rate also shows the increase in total costs in line with the increase in this parameter. By examining the outputs of 12 sample problems in large size, the WOA showed its efficiency compared to the ALO in terms of two indicators of average total costs and CPU time.
Keywords
Subjects

Aghighi, A., Goli, A., Malmir, B., & Tirkolaee, E. B. (2023). The stochastic location-routing-inventory problem of perishable products with reneging and balking. Journal of Ambient Intelligence and Humanized Computing, 1-20.
Aliahmadi, A., & Nozari, H. (2023, January). Evaluation of security metrics in AIoT and blockchain-based supply chain by Neutrosophic decision-making method. In Supply chain forum: an international journal (Vol. 24, No. 1, pp. 31-42). Taylor & Francis.
Aliahmadi, A., Jafari-Eskandari, M., Mozafari, M., & Nozari, H. (2013). Comparing artificial neural networks and regression methods for predicting crude oil exports. International Journal of Information, Business and Management, 5(2), 40-58.
Alvarez, A., Miranda, P., & Rohmer, S. U. K. (2022). Production routing for perishable products. Omega, 111, 102667.‏
Barma, P. S., Dutta, J., Mukherjee, A., & Kar, S. (2022). A multi-objective ring star vehicle routing problem for perishable items. Journal of Ambient Intelligence and Humanized Computing, 13(5), 2355-2380.‏
Chitsaz, M., Divsalar, A., & Vansteenwegen, P. (2016). A two-phase algorithm for the cyclic inventory routing problem. European Journal of Operational Research, 254(2), 410–426.
Eslamipoor, R. (2024). A new heuristic approach for a multi-depot three-level location-routing-inventory problem. International Journal of Management Concepts and Philosophy, 17(3), 322-339.
Ghaderi, A., Ghahremani Nahr, J., & Safari, S. (2024). Providing a Robust Heterogeneous Vehicle Fleet Routing Model Based on Artificial Intelligence of Things (AIoT). Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies).
Ghahremani-Nahr, J., Kian, R., Sabet, E., & Akbari, V. (2022). A bi-objective blood supply chain model under uncertain donation, demand, capacity and cost: a robust possibilistic-necessity approach. Operational Research, 22(5), 4685-4723.
Hiassat, A., Diabat, A., & Rahwan, I. (2017). A genetic algorithm approach for locationinventory-routingproblem with perishable products. Journal of Manufacturing Systems, 42, 93-103.
Hu, W., Toriello, A., & Dessouky, M. (2018). Integrated inventory routing and freight consolidation for perishable goods. European Journal of Operational Research, 271(2), 548-560.‏
Ji, Y., Du, J., Han, X., Wu, X., Huang, R., Wang, S., & Liu, Z. (2020). A mixed integer robust programming model for two-echelon inventory routing problem of perishable products. Physica A: Statistical Mechanics and its Applications, 548, 124481.‏
Karimi, Z., Ahmadi, P., Niaki, S. T. A., & Khakestari, M. (2023). A multi-criteria facility location-allocation of green supply chains with perishable items. International Journal of Services and Operations Management, 46(3), 393-428.
Keyvan, F., Saeid, J., & Ashkan, H. (2019). An extended robust approach for a cooperative inventory routing problem. Expert Systems with Applications, 116, 310–327.
Komijani, M., & Sajadieh, M. S. (2024). An integrated planning approach for perishable goods with stochastic lifespan: Production, inventory, and routing. Cleaner Logistics and Supply Chain, 12, 100163.
Liu, A., Zhu, Q., Xu, L., Lu, Q., & Fan, Y. (2021). Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model. Transportation Research Part E: Logistics and Transportation Review, 150, 102319.‏
Markov, I., Bierlaire, M., Cordeau, J. F., Maknoon, Y., & Varone, S. (2018). A unified framework for rich routing problems with stochastic demands. Transportation Research Part B, 114, 213–240.
Nasiri, M. M., Mousavi, H., & Nosrati-Abarghooee, S. (2023). A green location-inventory-routing optimization model with simultaneous pickup and delivery under disruption risks. Decision Analytics Journal, 6, 100161.
Navazi, F., Sazvar, Z., & Tavakkoli-Moghaddam, R. (2023). A sustainable closed-loop location-routing-inventory problem for perishable products. Scientia Iranica, 30(2), 757-783.
Nozari, H., & Nahr, J. G. (2022). The impact of blockchain technology and the internet of things on the agile and sustainable supply chain. International Journal of Innovation in Engineering, 2(2), 33-41.
Nozari, H., Tavakkoli-Moghaddam, R., Ghahremani-Nahr, J., & Najafi, E. (2023). A conceptual framework for Artificial Intelligence of Medical Things (AIoMT). In Computational Intelligence for Medical Internet of Things (MIoT) Applications (pp. 175-189). Academic Press.
Rabbani, M., Mokarrari, K. R., & Akbarian-saravi, N. (2021). A multi-objective location inventory routing problem with pricing decisions in a sustainable waste management system. Sustainable Cities and Society, 75, 103319.
Sayarshad, H. R., & Gao, H. O. (2018). A non-myopic dynamic inventory routing and pricing problem. Transportation Research Part E, 109, 83–98.
Song, L., & Wu, Z. (2023). An integrated approach for optimizing location-inventory and location-inventory-routing problem for perishable products. International Journal of Transportation Science and Technology, 12(1), 148-172.
Tirkolaee, E. B., & Aydin, N. S. (2022). Integrated design of sustainable supply chain and transportation network using a fuzzy bi-level decision support system for perishable products. Expert Systems with Applications, 195, 116628.
Yuchi, Q., Wang, N., He, Z., & Chen, H. (2021). Hybrid heuristic for the location‐inventory‐routing problem in closed‐loop supply chain. International Transactions in Operational Research, 28(3), 1265-1295.
Volume 15, Issue 2 - Serial Number 2
Spring 2023
Pages 112-123

  • Receive Date 04 January 2023
  • Revise Date 06 February 2023
  • Accept Date 26 March 2023