Specifying suboptimality tolerances can be useful if a decision maker wants to find a good but nor optimal solution to a complex ILP problem.

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Specifying suboptimality tolerances allows the decision maker to find a solution that is close to optimal but not necessarily the best possible solution, which can be useful for complex ILP problems where finding the true optimal solution may be computationally infeasible.

Specifying Suboptimality Tolerances Can Be Useful If a Decision Maker