Shadow prices represent the implicit value of a constraint in optimization problems, indicating how much the objective function would increase if that constraint were relaxed by one unit. They provide insights into resource allocation by revealing the trade-offs involved in decision-making, particularly in the context of constrained optimization, where resources are limited. Shadow prices are crucial for understanding how changes in constraints can affect overall outcomes, especially when dealing with equality constraints and dual problems.
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