it is a type of numeric constant which doesn't contain any fractional part
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It depends on the problem: you may have to use integer programming rather than linear programming.
N squared. It could be the Cartesian plane restricted to integer values, as required for integer linear programming problems.
In both cases the constraints are used to produce an n-dimensional simplex which represents the "feasible region". In the case of linear programming this is the feasible region. But that is not the case for integer programming since only those points within the region for which the variables are integer are feasible.The objective function is then used to find the maximum or minimum - as required. In the case of a linear programming problem, the solution must lie on one of the vertices (or along one line in 2-d, plane in 3-d etc) of the simplex and so is easy to find. In the case of integer programming, the optimal solution so found may contain one or more variables that are not integer and so it is necessary to examine all the points in the immediate neighbourhood and evaluate the objective function at each of these points. This last requirement makes integer programming solutions more difficult to find.
Integer programming offers several advantages, including the ability to model complex problems with discrete decision variables, which is useful for applications like scheduling and resource allocation. It guarantees optimal solutions under certain conditions, making it reliable for critical decision-making tasks. However, its disadvantages include computational complexity, as solving integer programming problems can be much harder than linear programming, leading to longer solving times. Additionally, the requirement for variables to take on integer values may limit the solution space and make it less flexible in some scenarios.
The values of the variables will satisfy the equality (rather than the inequality) form of the constraint - provided you are not dealing with integer programming.