Predicting Aluminum Consumption to Improve the Logistics Process Using an Agent-Based Model

Document Type : Research/ Original/ Regular Article

Authors

1 PhD Student in Industrial Management, Operations Research, Department of Industrial Management, Azadi Campus, Yazd University, Iran.

2 Industrial Management Department, Economics, Management & Accounting Faculty, Yazd University, Yazd.

3 Industrial Management Department, Economics, Management & Accounting Faculty, Yazd University, Yazd

4 Assistant prof., Department of Industrial Management, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran

Abstract

The primary objective of this study is to forecast future demand and improve logistics and raw material storage in the aluminum supply chain using a hybrid simulation approach. A 30-year dataset was used to forecast aluminum demand for the years 1403 to 1405 (Hijri Shamsi). To achieve this, a combination of discrete-event simulation (DES), system dynamics (SD), and agent-based modeling (ABM) was employed. Various probability distributions, mainly uniform and triangular, were applied based on modeling needs. The hybrid simulation model and sensitivity analysis show that the Iran Aluminum Company (IRALCO) supply chain can meet the projected demand increase over the next three years. The novelty of this research lies in integrating DES, SD, and ABM methodologies, enabling a more comprehensive and layered analysis of supply chain behavior. This integrated approach sets the study apart from previous research. The study adopts a mixed-methods design: the conceptual model was developed qualitatively, while quantitative techniques were used for model analysis. In light of resource constraints and the strategic importance of domestic aluminum supply, this research emphasizes innovative demand forecasting methods. Hybrid simulation is considered a suitable and underutilized tool in the literature, contributing to both theoretical advancement and methodological development. The high accuracy of forecasts derived through this approach underscores its effectiveness. Results highlight the significant roles of road and rail logistics, as well as warehousing, in enhancing supply chain performance.

Keywords

Main Subjects

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Supply Chain Management
Volume 27, Issue 89 - Serial Number 89
Serial number 89. Winter 2026
December 2026
Pages 27-46

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History

  • Receive Date: 05 May 2025
  • Revise Date: 03 September 2025
  • Accept Date: 07 September 2025
  • Publish Date: 20 February 2026

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