# ADMS 3330 Study Guide - Feasible Region, Decision Analysis

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**1.** The following is a linear programming formulation of a labor planning problem. There are four overlapping shifts, and management must decide how many employees to schedule to start work on each shift. The objective is to minimize the total number of employees required while the constraints stipulate how many employees are required at each time of day. The variables X_{1} - X_{4} represent the number of employees starting work on each shift (shift 1 through shift 4).

Minimize X_{1} + X_{2} + X_{3} + X_{4}

Subject to: X_{1} + X_{4}%u2265 12 (shift 1)

X_{1} + X_{2}%u2265 15 (shift 2)

X_{2} + X_{3}%u2265 16 (shift 3)

X_{3} + X_{4}%u2265 14 (shift 4)

all variables %u2265 0

Find the optimal solution using QM.

How many workers would be assigned to shift 1? (Points : 3) 12

13

0

none of the above

moving the isoprofit lines towards the origin in a parallel fashion until the last point in the feasible region is encountered. locating the point that is highest on the graph. none of the above. all of the above. |

equal to linear to parallel to |

maximize ingredient blends. minimize production losses. maximize the number of products to be produced. minimize the costs of nutrient blends. |

different product mix, same total profit as before. same product mix, same total profit. different product mix, different total profit. |

requires that the profit from all corners of the feasible region be compared. will provide one, and only one, optimum. requires that all corners created by all constraints be compared. will not provide a solution at an intersection or corner where a non-negativity constraint is involved. |

1200 360 none of the above |

putting in a value for the objective function. choosing the options for assuming both a linear model and non-negative variables. resetting the parameters. none of the above. |

(20,50) (60,30) none of the above |

10. ____________ is used to analyze changes in model parameters. (Points : 3) |

Feasible solution

Sensitivity analysis

None of the above