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Linear Programming Theory And Solver Output/Sensitivity Report 1.How pile a linear program terminate? 1.Unique best Solution 2.In practicable -- Solver Could not find a feasible solution 3.Unbounded The Set Cell values do not converge 4.Alternate Optimal Solutions An allowable increase or accrue for an aim power coefficient = 0 2.What points can be optimal? 1. thoroughgoing Points (An extreme point is always optimal) 2.Boundary Points (When there ar alternate optimal solutions) 3.What is the meaning of a cut back speak to? For multivariates that are positive reduced cost = 0 For variables that are 0, the reduced cost means 1.The amount that accusive function coefficient must stir before that variable can become positive. 2.The amount the objective function value would change if that variable were increased from 0 to 1. 4.What is the regularise of optimality for an objective function coefficient?

It is the cast from (current value of the objective function coefficient) (ALLOWABLE DECREASE) to (current value of the objective function coefficient) + (ALLOWABLE INCREASE) In this range the optimal solution will not change In this range the optimal profit will change if the coefficient multiplies a variable that is positive in the optimal solution 5.What is unlax or otiose? Slack = (RHS coefficient) (LHS value) for ? coldnesss Surplus = (LHS value) (RHS coefficient) for ? constraints 6.What is a shadow price? For constraints whose slack or surplus ? 0, the shadow price = 0. For constraints whose slack or surplus = 0, the shadow price = the value the objective function value will change per unit change in the RHS coefficient (within the range of feasibility) The actual interpretation depends on whether the resource for the constraint was included in calculating the original... If you want to get a full essay, order it on our website: Ordercustompaper.com

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