Integer Linear Programming (ILP) is a type of optimization problem where the objective function and constraints are linear, but some or all of the decision variables are required to take integer values.

Integer Linear Programming (ILP) is a mathematical optimization technique where the objective is to maximize or minimize a linear function subject to a set of linear constraints, with the added requirement that some or all of the decision variables must take on integer values. This approach is particularly useful in scenarios where decisions are discrete, such as in scheduling, resource allocation, and logistics. ILP problems are formulated with a linear objective function, constraints that are also linear equations or inequalities, and the integrality constraints that specify which variables must be integers. Because of the integer constraints, ILP problems can be more challenging to solve than standard linear programming problems, which allow for continuous variables.