Many practical problems in operations research can be expressed as linear programming problems. Certain special cases of linear programming, such as network flow problems and multicommodity flow problems, are considered important enough to have much research on specialized algorithms.

In operations research, special cases in linear programming—such as **infeasibility, unboundedness, redundancy,** and **alternate optimal solutions**—help identify and address issues in decision-making. These special cases guide adjustments in constraints, objective functions, or resource allocations to ensure realistic, practical solutions that optimize performance or costs. Understanding these cases enhances decision-making by pinpointing potential problems and offering insights for refining models.