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@article{177072,
        author = {Amit Ghosh and Dr. Manish Kumar Singh},
        title = {A LINEAR PROGRAMMING-BASED APPROACH TO PRODUCTION OPTIMIZATION IN OIL REFINING OPERATIONS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {157-168},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177072},
        abstract = {The petroleum refining industry plays a critical role in converting crude oil into essential products such as gasoline, diesel, and petrochemicals, which are vital for global energy needs. However, refineries face numerous challenges, including fluctuating crude oil prices, stringent environmental regulations, and the need for efficient resource utilization. This paper explores the application of Linear Programming (LP) as a powerful optimization tool for improving production efficiency in oil refining operations. By formulating LP models, refineries can optimize crude oil blending, production scheduling, energy consumption, and ensure compliance with quality and environmental constraints. Through case studies and real-world examples, the paper demonstrates how LP-based approaches lead to cost reductions, increased profitability, and enhanced sustainability. Moreover, the paper discusses future trends, including the integration of artificial intelligence (AI), machine learning, and renewable energy sources, which hold the potential to further improve the precision and effectiveness of LP models in refining operations. This research highlights the significant benefits of LP in streamlining refinery processes, providing refineries with a robust framework for making informed, data-driven decisions in an increasingly competitive and regulated industry.},
        keywords = {Linear programming, production optimization, oil refining, cost minimization, resource allocation, supply chain management, refinery operations, process constraints, product demand, operational efficiency, mathematical modeling, optimization techniques.},
        month = {April},
        }