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What is the difference between a reduced cost and a shadow price in linear programming?

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In linear programming, reduced cost is the amount by which the objective function coefficient must improve before a non-basic variable enters the solution, while shadow price represents the rate of improvement in the objective function when a constraint's right-hand side increases by one unit.


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