Application of Research in Project Operations And Investment

Document Type : Original Article

Authors
Kamran Yeganegi 1
Seyedeh Sara Ghamari 2
1 Department of Industrial Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
2 MA student, Department of Management, Zanjan Branch, Zanjan Azad University, Zanjan, Iran
10.22034/jmek.2024.429462.1116
Abstract
Operations Research (OR), utilizing methods such as mathematical modeling to analyze complex conditions, consistently empowers executive managers to make more appropriate decisions and create efficient, optimal, and productive systems. This study aims to investigate the application of Operations Research techniques in project investment and its role in optimizing financial and managerial decisions. Employing a review and analytical approach, this study examines the literature and background of research conducted on the integration of mathematical modeling, optimization, and risk analysis in investment projects. In this regard, various types of investment projects, associated risks, and their limitations are evaluated, and OR techniques for cost management, scheduling, and risk reduction are introduced. The findings indicate that the investor, as the project champion, evaluates investment opportunities to determine the Return on Investment (ROI), which is a key project performance metric. The application of OR tools, such as linear programming, network analysis, and stochastic models, provides the capability for accurate outcome prediction, risk assessment, optimal resource allocation, and cost reduction under complex conditions and uncertainty. The utilization of mathematical modeling in solving real-world investment problems leads to determining the best possible decision, increasing productivity, improving business performance, and ultimately creating sustainable value and profitability for organizations and the society's economy.
Keywords
Operations Research
Mathematical Modeling
Project Investment
Optimization
Risk Management
Subjects
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  • Receive Date 08 March 2026
  • Revise Date 02 May 2026
  • Accept Date 21 July 2026