Practical Management Science
Practical Management Science
6th Edition
ISBN: 9781337671989
Author: WINSTON
Publisher: Cengage
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Chapter 12.5, Problem 20P
Summary Introduction

To determine: The number of tellers that the bank should hire.

Introduction: In order to predict the waiting time and length of the queue, queueing model will be framed. Queueing theory is the mathematical model that can be used for the decision-making process regarding the resources required to provide a service.

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The Harvey Motorcycle Company produces three models: the Tiger, a sure-footed dirt bike; the LX2000, a nimble cafe racer; and the Golden, a large interstate tourer. The month's master production schedule calls for the production of 32 Goldens, 31 LX2000s, and 38 Tigers per 10-hour shift. What average cycle time is required for the assembly line to achieve the production quota in 10 hours? 0.099 hours per motorcycle. (Enter your response rounded to three decimal places.) If mixed-model scheduling is used, how many of each model will be produced before the production cycle is repeated? The greatest common divisor of the production requirements is Therefore, the Harvey Motorcycle Company will produce Goldens, LX2000s, and Tigers. (Enter your responses as integers.)
The Harvey Motorcycle Company produces three models: the Tiger, a sure-footed dirt bike; the LX2000, a nimble cafe racer; and the Golden, a large interstate tourer. The month's master production schedule calls for the production of 32 Goldens, 31 LX2000s, and 38 Tigers per 10-hour shift. What average cycle time is required for the assembly line to achieve the production quota in 10 hours? hours per motorcycle. (Enter your response rounded to three decimal places.)
The binding constraints for this problem are the second and third constraints are binding. Min x1 + 2x2 s.t. x1 + x2 ≤ 300 2x1 + x2 ≥ 400 2x1 + 5x2 ≥750 X1, X220 (a) Keeping the second objective function coefficient fixed at 2, over what range can the first objective function coefficient vary before there is a change in the optimal solution point? The first objective coefficient can from a low of to a high of (b) Keeping the first objective function coefficient fixed at 1, over what range can the second objective function coefficient vary before there is a change in the optimal solution point? The second objective coefficient can from a low of to a high of (c) If the objective function becomes Min 1.5x₁ + 2x2, what will be the optimal values of x1 and x2? x1 = X2 = What is the value of the objective function at the minimum? (d) If the objective function becomes Min 7x₁ + 6x2, what constraints will be binding? (Select all that apply.) First Constraint Second Constraint Third Constraint…
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