Lisa makes two sorts of jewelry- Type A and Type B. Type A requires 90 minutes of curving and 1hours of assembly time.  On the other hand,   Type B requires 45 minutes of curving and 2 hours of assembly time. Lisa can sell Type A for $12 and Type B for $55. Given that Lisa has only 1000 hours of curving 500 hours of assembly time. How many of each type of Jewelry Lisa should make to maximize revenue? Keep in mind that Type A jewelry has to be at least twice the number of Type B jewelry. (Possible Answer: $9875) (Suggestion: Convert all the hours to minutes so that you do not end up mixing hours and minutes)   CAN YOU DO THIS QUESTION IN THIS TEMPLATE  ?    Data             Curving Assembly Price   A 1.5 1  $          12.00   B 0.75 2  $          55.00                                                                                           Model                   Decision Variables                   A 0 X     B 0 Y                                 Objective Function                   MAX($)  $                 -                           Constraints         LS Relation RS [Name]   0 GTE 0 [NN X]   0 GTE 0 [NN Y]   0 LTE 1000 [CURVING]   0 LTE 500 [ASSEMBLY]   0 LTE 0 [RATIO]

Practical Management Science
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ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
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Lisa makes two sorts of jewelry- Type A and Type B. Type A requires 90 minutes of curving and 1hours of assembly time.  On the other hand,   Type B requires 45 minutes of curving and 2 hours of assembly time.

  • Lisa can sell Type A for $12 and Type B for $55. Given that Lisa has only 1000 hours of curving 500 hours of assembly time. How many of each type of Jewelry Lisa should make to maximize revenue? Keep in mind that Type A jewelry has to be at least twice the number of Type B jewelry. (Possible Answer: $9875)

(Suggestion: Convert all the hours to minutes so that you do not end up mixing hours and minutes)

 

CAN YOU DO THIS QUESTION IN THIS TEMPLATE  ? 

 

Data        
    Curving Assembly Price
  A 1.5 1  $          12.00
  B 0.75 2  $          55.00
         
         
         
         
         
         
         
         
         
Model        
         
Decision Variables      
         
  A 0 X  
  B 0 Y  
         
         
         
Objective Function      
         
  MAX($)  $                 -      
         
         
Constraints        
LS Relation RS [Name]  
0 GTE 0 [NN X]  
0 GTE 0 [NN Y]  
0 LTE 1000 [CURVING]  
0 LTE 500 [ASSEMBLY]  
0 LTE 0 [RATIO]  
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