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Linear Programming (LP) and Optimization Models are powerful mathematical tools used to find the best possible solution to problems involving limited resources and competing objectives. Linear Programming focuses on optimizing a linear objective function—such as minimizing costs or maximizing profits—subject to a set of linear constraints that represent real-world limitations like budgets, labor, or materials. Optimization models extend this idea by providing structured frameworks to analyze complex decision-making scenarios, ensuring efficiency and effectiveness in operations. These models are widely applied in industries such as manufacturing, transportation, finance, and supply chain management, where they help organizations allocate resources, schedule tasks, and design systems for maximum productivity. In essence, LP and optimization models transform decision-making into a systematic, quantitative process that balances constraints with desired outcomes.
This lecture is part of KWASU CSC 206 OPERATION RESEARCH in the Computer Science department. The course has 15 recorded lectures across 5 series, all free to watch.