Simplex Method
The Simplex Method is an algorithm for solving linear programming problems, which involve optimizing a linear objective function subject to linear equality and inequality constraints. It works by iteratively moving from one vertex (or extreme point) of the feasible region to an adjacent one with a better objective value until an optimal solution is found. Developed by George Dantzig in 1947, it is widely used in operations research, economics, and engineering for resource allocation, scheduling, and optimization tasks.
Developers should learn the Simplex Method when working on optimization problems in fields like logistics, finance, or machine learning, where linear programming models are common. It is essential for solving real-world problems such as maximizing profit, minimizing costs, or allocating resources efficiently under constraints. Understanding this algorithm helps in implementing or using optimization libraries and tools in software applications.