Set up Excel model as follows:
Set up Solver Parameters as follows:
Click Solve to generate the solution.
After that, values appear automatically in variable (yellow colored) cells
Click OK
Optimal schedule of buses is :
Starting time | Number of buses |
12:01 AM | 4 |
4:01 AM | 4 |
8:01 AM | 6 |
12:01 PM | 1 |
4:01 PM | 11 |
8:01 PM | 0 |
Total number of buses = 26
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WORKFORCE PLANNING-BUS SCHEDULING MODEL Example 2.4.5 on page 68 of Taha's book Number of busses as a function of the time of the day: MOD AM * Number of art 1201 Xe Number of buses strihy at 4:01am *Number of buses starting at 8: lam Number of buses kurting at 12:01 : Number of buses starting at 4:01pm Number of buses starting at 1pm 33
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MULTI-PERIOD PRODUCTION-INVENTORY MODEL Example 2.4.3 on page 64 of Taha's book Acme Manufacturing Company has contracted to deliver home windows over the next 6 months. نما 4 Month Demand Production Cost per window 100 $50 250 $45 190 $55 140 $48 5 220 $52 6 110 $50 To take advantage of the fluctuations in manufacturing cost, Acme may select to produce more than needed in a given...
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MULTI-PERIOD PRODUCTION-SMOOTHINGG MODEL Example 2.4.4 on page 65 of Taha's book A company will manufacture a product for the next four months: March, April, May, and June The demands for each month are 520, 720, 520, and 620 units, respectively. • The company has a steady work force of 10 employees but can meet fluctuating production needs by hiring and firing temporary workers at the beginning of each month, if necessary...
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URBAN PLANNING - URBAN RENEWAL MODEL Example 2.4.6 on page 70 of Taha's book Decision variables: XI-Number of units of single-family homes x2 - Number of units of double-family homes x3 = Number of units of triple-family homes x4 - Number of units of quadruple-family homes xs = Number of old homes to be demolished XS Maximize z=1000 x1 + 1900 x2 +2700 x3 +3400 x4 Subject...
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MULTI-PERIOD PRODUCTION-SMOOTHINGG MODEL Example 2.4.4 on page 65 of Taha's book • A company will manufacture a product for the next four months: March, April, May, and June. The demands for each month are 520, 720, 520, and 620 units, respectively. • The company has a steady work force of 10 employees but can meet fluctuating production needs by hiring and firing temporary workers at the beginning of each month,...
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MULTI-PERIOD PRODUCTION-SMOOTHINGG MODEL Example 2.4.4 on page 65 of Taha's book A company will manufacture a product for the next four months: March, April, May, and June The demands for each month are 520, 720, 520, and 620 units, respectively. • The company has a steady work force of 10 employees but can meet fluctuating production needs by hiring and firing temporary workers at the beginning of each month, if necessary The extra costs...
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쇠 Hw4(4).pdf-Aciooe Acrobat Redder DC File Edit V Window Help Home Tools Nvaldo J. Tro - Ch Sign In t1 Share 1) As you are rnning you think of a clever t-shirt design. You decide to get the t-shirts printed profession- ally with the intention of seling them to make a profit. The table bclow outlincs the cost (in $) of getting a certain number (N) of t-shirts printed Export PDF Create...
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BoyuQuCh7CaseStudy - Excel File Insert Page Layout Formulas Data Review View Add-ins ACROBAT QuickBooks Tell me what you want to do Sign in Share Σ Autosum Calibri Fill Paste в ㅣ u . re. O . . _ Ξ_ 트트 분 Merge & Center. $. % , 'i..g Conditional Format as Cell Insert Delete Format Sort & Find & Filter Select Formatting Table Styles Clipboard Font Alignment Number Cells Editing E3 Input Area Calculations 2 Facility...
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466-566-P12020(2) - Protected View - Saved to this PC 18109361685 A Share P Comments Mailings P Tell me what you want to do File Draw Design References View Help Home Insert Layout Review Please prepare according to the "Problem Set Guidelines" in the "Course Documents" section, and submit your solutions in the Assignments section of Blackboard by Sunday, January 19 at 11:59 p.m. There is...
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D. and the standard deviation of this distribution. 71. FILE Refer to the Baseball 2016 data. Compute the mean number of home runs per game. To do this, first find the mean number of home runs per team for 2016. Next, divide this value by 162 (a season comprises 162 games). Then multiply by 2 because there are two teams in each game. Use the Poisson distribution to estimate the...