In this example, you will note that the allowable increase for decision variable A (tables) is a very large number and the allowable increase for decision variable B (chairs) is 290. However if the objective coefficient increases by an amount greater than 13.58, you will see that the final value for decision A will change from what is optimal now. In other words, if the objective coefficient of decision A increases by an amount less than the allowable increase, the recommended solution to the model/problem (optimal decision variables) will not change. The allowable increase and allowable decrease values tell you how much the objective coefficient of a decision variable can change before the recommended solution (decision variables) will change. Allowable Increase And Allowable Decrease The reduced cost discussed above has considered the opportunity cost of producing that unit too. However, this Objective Coefficient value has not considered the opportunity cost of producing one additional unit.
The Objective Coefficient of 328 indicates that for each unit of decision variable A, which is the number of tables we produce in this example, your profit went up by 328. The profits considered the revenues and costs of machine time and material. You were trying to maximize profits in this example. The Objective Coefficient is the coefficient of the decision variables in the linear programing equation that you set up and ran on solver. The objective value in this example is profits and so we would see a reduction in profits of 13.58 if we produce one additional table. A reduced cost of -13.58, would indicate that a one unit increase in the final value of the tables decision will result in a decrease of the objective value by 13.58. Let us see how we can interpret the reduced cost if the reduced cost for the number of tables we produce was instead a negative value: -13.58. The reduced cost for decision variable A in this example is zero. The reduced cost value for each decision variable tells you how much your objective function value will change for a one unit increase in that decision variable. The primary values of interest in the variable cells section of the sensitivity report are the “Reduced Cost” values for each of the decision variables chosen in the linear programing model. The Sensitivity Report of a LP Solver Model Variable Cells Section in the Sensitivity Report What does the Reduced Cost Tell Us?
The variable cells and constraints section. The sensitivity report is broken down into two parts. It is very useful for managerial decisions. The Sensitivity Report is the most useful of the three reports. We will look at the Answer Report, Sensitivity Report and Limits Report one by one starting with the Sensitivity Report.
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This article shows you how to interpret a linear programing model’s Sensitivity Report, Answer Report and Limits Report. Solver reports include a Sensitivity Report, an Answer Report and a Limits Report. Interpreting the linear programing model’s solver reports present another challenge. Performing a linear programing model is one challenge. All MBA students will encounter linear programing in one or more operations management courses in business school.
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