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Integer Programming

Integer programming is a mathematical optimization technique where some or all variables are restricted to integer values, used to model discrete decision-making problems. It extends linear programming by adding integer constraints, making it suitable for problems involving whole units like scheduling, routing, or resource allocation. This method is widely applied in operations research, logistics, and computer science to find optimal solutions under discrete conditions.

Also known as: IP, Integer Linear Programming, ILP, Mixed-Integer Programming, MIP
🧊Why learn Integer Programming?

Developers should learn integer programming when tackling optimization problems with discrete variables, such as in supply chain management, network design, or project scheduling, where fractional solutions are impractical. It is essential for applications like vehicle routing, workforce planning, or combinatorial optimization in algorithms, providing exact solutions where continuous approximations fail. Mastery is valuable in fields like data science, AI planning, and industrial engineering for solving complex real-world constraints efficiently.

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