What is the significance of the integrality constraint in ILP?
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The integrality constraint in Integer Linear Programming (ILP) ensures that decision variables take on only integer values, which is crucial for modeling real-world scenarios where solutions must represent discrete quantities, such as items produced or resources allocated, thereby leading to more practical and implementable outcomes.
The integrality constraint in ILP ensures that decision variables take integer values, which is crucial for accurately modeling real-world problems where fractional solutions are not feasible, such as in scheduling, assignment, or resource allocation.
The integrality constraint ensures that the solutions are discrete and applicable in scenarios where fractional values do not make sense, such as the number of items produced, vehicles dispatched, or people assigned to tasks.