Combinatorial optimization is a branch of optimization that deals with problems where the set of feasible solutions is discrete or can be reduced to a discrete set. Its goal is to find the best solution according to a specific criterion, often under constraints. From scheduling tasks to designing networks and solving puzzles like Sudoku, combinatorial optimization plays a crucial role in solving real-world problems.
The Conjugate Gradient method is an iterative algorithm for efficiently solving large sparse systems of linear equations, specifically those with a symmetric positive definite matrix from conservation problems arising in many fields of science and engineering, economics, finance and operations research.
