Presentation of a Mathematical Model for Optimizing the Production Scheduling of Lubricant Products

Document Type : Research Paper

Authors

1 Master of Industrial Engineering, Department of Socio-Economic Systems, Faculty of Industrial Engineering, Tarbiat Modares University, Tehran, Iran

2 Associate Professor, Department of Socio-Economic Systems, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

3 Associate Professor, Department of Systems and Productivity Management, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

10.22084/ier.2025.29548.2172

Abstract

Nowadays, production planning and scheduling have become the core of production management in manufacturing systems, as they lead to greater profitability and stabilization of daily output. In some manufacturing industries, the production process is continuous and operates at high capacity. Therefore, making optimal decisions for sustainable production and maximizing company profit is essential. The problem of production planning and scheduling in continuous manufacturing systems that produce various products, considering operational constraints for different products to meet customer demand, is one of the complex yet important issues in manufacturing industries—particularly in the production of lubricant products. In this study, considering the structure of lubricant production, a model is developed and optimized for production scheduling. The goal is to optimize scheduling and provide an execution sequence for the production plan, while taking into account tank inventory levels and capacity constraints. The validity of the proposed model is verified using real data. The formulated mathematical model has been implemented in the GAMS optimization software, and the optimal solution(s) has been obtained within an acceptable runtime. The results demonstrate improvements in scheduling and indicate the applicability of the proposed model in real-world scenarios.

Keywords

Main Subjects

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Journal of Industrial Engineering Research in Production Systems
Volume 12, Issue 25
March 2025
Pages 5-17

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