Constrained optimization is a research area in mathematics and computer science that focuses on finding the optimal solution of a problem subject to a set of constraints or restrictions. These constraints can be inequalities, equalities, or a combination of both, and they limit the possible values that the variables in the optimization problem can take. Constrained optimization algorithms aim to efficiently search for the best solution within the constraints, often using techniques such as linear programming, quadratic programming, or nonlinear programming. This research area is widely used in various fields such as engineering, economics, finance, and operations research to solve complex real-world problems efficiently and effectively.