In aggregate planning models, we can model backlogging of demand by allowing a month's inventory to be negative. a. True b. False . Suppose the allowable increase and decrease for an objective coefficient of a decision variable that has a current value of $50 are $25 (increase) and $10 (decrease). If the coefficient were to change from $50 to $65, the optimal value of the objective function would not change. a. True b. False Shadow prices are associated with binding constraints and show the change in the optimal objective function value when the right side of the constraint equation changes by one unit.

In aggregate planning models, we can model backlogging of demand by allowing a month's inventory to be negative. a. True b. False . Suppose the allowable increase and decrease for an objective coefficient of a decision variable that has a current value of $50 are $25 (increase) and $10 (decrease). If the coefficient were to change from $50 to $65, the optimal value of the objective function would not change. a. True b. False Shadow prices are associated with binding constraints and show the change in the optimal objective function value when the right side of the constraint equation changes by one unit.

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter12: Queueing Models

Section12.3: The Exponential Distribution

Problem 3P

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In Example 11.3, suppose you want to run five simulations, where the probability of passing inspection is varied from 0.6 to 1.0 in increments of 0.1. Use the RISKSIMTABLE function appropriately to do this. Comment on the effect of this parameter on the key outputs. In particular, does the probability of passing inspection have a large effect on when production should start? (Note: When this probability is low, it might be necessary to produce more than 25 batches, the maximum built into the model. Check whether this maximum should be increased.)
It costs a pharmaceutical company 75,000 to produce a 1000-pound batch of a drug. The average yield from a batch is unknown but the best case is 90% yield (that is, 900 pounds of good drug will be produced), the most likely case is 85% yield, and the worst case is 70% yield. The annual demand for the drug is unknown, with the best case being 20,000 pounds, the most likely case 17,500 pounds, and the worst case 10,000 pounds. The drug sells for 125 per pound and leftover amounts of the drug can be sold for 30 per pound. To maximize annual expected profit, how many batches of the drug should the company produce? You can assume that it will produce the batches only once, before demand for the drug is known.
Big Hit Video must determine how many copies of a new video to purchase. Assume that the companys goal is to purchase a number of copies that maximizes its expected profit from the video during the next year. Describe how you would use simulation to shed light on this problem. Assume that each time a video is rented, it is rented for one day.
Assume that all of a companys job applicants must take a test, and that the scores on this test are normally distributed. The selection ratio is the cutoff point used by the company in its hiring process. For example, a selection ratio of 25% means that the company will accept applicants for jobs who rank in the top 25% of all applicants. If the company chooses a selection ratio of 25%, the average test score of those selected will be 1.27 standard deviations above average. Use simulation to verify this fact, proceeding as follows. a. Show that if the company wants to accept only the top 25% of all applicants, it should accept applicants whose test scores are at least 0.674 standard deviation above average. (No simulation is required here. Just use the appropriate Excel normal function.) b. Now generate 1000 test scores from a normal distribution with mean 0 and standard deviation 1. The average test score of those selected is the average of the scores that are at least 0.674. To determine this, use Excels DAVERAGE function. To do so, put the heading Score in cell A3, generate the 1000 test scores in the range A4:A1003, and name the range A3:A1003 Data. In cells C3 and C4, enter the labels Score and 0.674. (The range C3:C4 is called the criterion range.) Then calculate the average of all applicants who will be hired by entering the formula =DAVERAGE(Data, "Score", C3:C4) in any cell. This average should be close to the theoretical average, 1.27. This formula works as follows. Excel finds all observations in the Data range that satisfy the criterion described in the range C3:C4 (Score0.674). Then it averages the values in the Score column (the second argument of DAVERAGE) corresponding to these entries. See online help for more about Excels database D functions. c. What information would the company need to determine an optimal selection ratio? How could it determine the optimal selection ratio?
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you own a furniture store and you are in the process of planning the production of wooden chairs for the next six months. your demand forecast for wooden chairs for the next six months is 150,100,200,300,50,200. you currently stock 50 chairs in stock. one of your customers informed you that they would be returning 50 additional chairs to you and you expect to receive these returns in month 2. you currently employ 10 skilled employees who work entirely making chairs. in the last six months they were able to make 900 chairs working full time. you are considering two alternative production plans: constant workforce level for the next six months and meet all demand on time. adjust your workforce level only once over the next six months after month 0. ( no still backlogging). hiring cost per employee=$1000holding cost monthly per chair=$10 lay off cost per emloyee=$2000payroll cost monthly per employee=$2000 implement each alternative to obtain the least total cost. solve this question…
you own a furniture store and you are in the process of planning the production of wooden chairs for the next six months. your demand forecast for wooden chairs for the next six months is 150,100,200,300,50,200. you currently stock 50 chairs in stock. one of your customers informed you that they would be returning 50 additional chairs to you and you expect to receive these returns in month 2. you currently employ 10 skilled employees who work entirely making chairs. in the last six months they were able to make 900 chairs working full time. you are considering two alternative production plans: constant workforce level for the next six months and meet all demand on time. adjust your workforce level only once over the next six months after month 0. ( no still backlogging). hiring cost per employee=$1000holding cost monthly per chair=$10 lay off cost per emloyee=$2000payroll cost monthly per employee=$2000 implement each alternative to obtain the least total cost. solve this question with…
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13) Which of the following method is used for calculating Time value of Money? a. Future Value b. All of the options c. Annuity method d. Present value
Which of the following is NOT a determinant of the demand for good X?

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	a.	Flow in ≥ Flow out + Net supply
	b.	Flow out ≥ Flow in + Net demand
	c.	Flow in = Flow out
	d.	Flow out ≤ Flow in + Net supply
	e.	Flow in ≤ Flow out + Net demand