Designing a Agent-based model for production optimization and inventory control and routing in the supply chain of perishable products.
Subject Areas : Industrial Management
Mehdi Sohanian
1
,
رضا احتشام راثی
2
,
Reza Radfar
3
1 - PhD student in industrial management (systems), Faculty of Management and Economics, Science and Research Department, Islamic Azad University, Tehran, Iran
2 - Assistant Professor, Department of Industrial Management, Faculty of Management and Economics, Qazvin Branch, Islamic Azad University, Qazvin,
3 - Department of Industrial Management, Faculty of Management and Economics, Islamic Azad University, Tehran Science and Research Unit, Tehran, Iran
Keywords: supply chain, perishable products, discrete event simulation, Agent-based modeling, optimization,
Abstract :
The purpose of this research is to present a combined agent-based and discrete event model to investigate integrated production planning, inventory control, and the number and types of vehicles in the supply chain for perishable products. The agent-based model is employed to assess the role of various factors and their interrelationships within the supply chain. To account for the micro-level complexities of production lines, a discrete event simulation approach is utilized.To determine optimal or near-optimal production levels, inventory control, and the number and types of vehicles, a simulation-optimization approach is adopted, utilizing meta-heuristic and modeling algorithms in AnyLogic software. The simulation focuses on the production and routing of eight ice cream products distributed across three cold storage facilities. A total of 42 vehicles from four different types are used for transporting the products. To validate the model, discrepancies between actual values and those predicted by the model are assessed based on four key metrics: the quantity of products produced over one year, the number of shipments dispatched to distributors, the number of cooling system failures of machinery, and the count of products that recycle due to spoiled conditions. As all discrepancies for these four metrics are less than five, the validity of the model is confirmed.The results indicate that the objective function improves by 3%, while the average time from order receipt to product delivery is reduced by 5%. In the first scenario, product production is modeled based on the minimum and maximum available quantities as well as the minimum and maximum simulation values. In the second scenario, the number of vehicles is initially set at 42 but is reduced to 37 based on the proposed adjustments. Furthermore, the establishment of a new warehouse in Isfahan is recommended. With this new facility, the time interval from order receipt to delivery to distributors is expected to decrease to 131.6 hours. Additionally, considering the increase in production, the suggested optimal number of vehicles required for efficient operation is 44.
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