Operations Research : Applications and Algorithms
Operations Research : Applications and Algorithms
4th Edition
ISBN: 9780534380588
Author: Wayne L. Winston
Publisher: Brooks Cole
Question
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Chapter 6, Problem 37RP
Program Plan Intro

Optimal solution:

  • Here, consider the LP:
  • min z=400x1+400x2+400x3+400x4+450y1+450y2+450y3+450y4+20i1+20i2+20i3+20i4
  • Subject to constraints:
  • x1,x2,x3,x440
  • i1=10+x1+y140, i2=i1+x2+y260
  • i3=i2+x3+y375, i4=i3+x4+y425
  • it,yt,xt0
  • Where
  • xt= Number of sailboats produced by regular time labor during quarter t.
  • yt= Number of sailboats produced by overtime labor during
  • it= Number of sailboats on hand at end of quarter t.
  • In order to calculate the optimal solution of the primal, use the software Lindo
  • Step 1:
    • Type in the Linear Program in the command window. Select yes when asked about the range analysis.
  • The output is shown below:
  • LP optimum found at step 7
  • Objective function value: 78450
VariableValueReduced Cost
x140.0000000.000000
x240.0000000.000000
x340.0000000.000000
x425.0000000.000000
y10.00000020.000000
y210.0000000.000000
y335.0000000.000000
y40.00000050.000000
i110.0000000.000000
i20.00000020.000000
i30.00000070.000000
i40.000000420.000000
RowSlack or SurplusDual prices
20.00000030.000000
30.00000050.000000
40.00000050.000000
515.0000000.000000
60.000000-430.000000
70.000000-450.000000
80.000000-450.000000
90.000000-400.000000
  • Number of iterations=7
  • Ranges in which the basis is unchanged:
Obj coefficient ranges
VariableCurrent coefficientAllowable increaseAllowable decrease
x1400.00000030.000000Infinity
x2400.00000050.000000Infinity
x3400.00000050.000000Infinity
x4400.00000050.000000400.000000
y1450.000000Infinity20.000000
y2450.00000020.00000020.000000
y3450.00000020.00000050.000000
y4450.000000Infinity50.000000
i120.00000030.00000020.000000
i220.000000Infinity20.000000
i320.000000Infinity70.000000
i420.000000Infinity420.000000
Righthand side ranges
RowCurrent RHSAllowable increaseAllowable decrease
240.00000010.00000010.000000
340.00000010.00000040.000000
440.00000035.00000040.000000
540.000000Infinity15.000000
630.00000010.00000010.000000
760.000000Infinity10.000000
875.000000Infinity35.000000
925.00000015.00000025.000000
  • Therefore, the optimal solution of primal is given by
  • z=78450,x1=x2=x3=40,x4=25,y1=0,y2=10,y3=35,y4=0,i1=10,i2=i3=i4=0

Explanation of Solution

b.

  • It can be seen from the Lindo output that the Obj coefficient ranges block is used to determine the amount by which each variable’s objective function coefficient may change before the current basis becomes suboptimal.
  • If the objective function coefficient for c1 is increased above 400+30=430. Now the current basis is no longer optimal.
  • Since, Δc1=20 and the allowable increase is 30, the current basis remains optimal. The optimal values of the decision variables remain unchanged, that is,
  • x1=x2=x3=40,x4=25,y1=0,y2=10,y3=35,y4=0,i1=10,i2=i3=i4=0
  • The new optimal z-value can be obtained by substituting the substituting the optimal values of the decision variables

Explanation of Solution

c.

  • If the demand of the sailboat increases by 1 unit in the first quarter, then the cost would increase by $430.
  • As it can be observed from row (6) Dual prices section of the Lindo output.
  • Since, the amount offered is less than the rise in the total cost, there is no incentive for Sailco to cater to this new demand...

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Chapter 6 Solutions

Operations Research : Applications and Algorithms

Ch. 6.3 - Prob. 4PCh. 6.3 - Prob. 5PCh. 6.3 - Prob. 6PCh. 6.3 - Prob. 7PCh. 6.3 - Prob. 8PCh. 6.3 - Prob. 9PCh. 6.4 - Prob. 1PCh. 6.4 - Prob. 2PCh. 6.4 - Prob. 3PCh. 6.4 - Prob. 4PCh. 6.4 - Prob. 5PCh. 6.4 - Prob. 6PCh. 6.4 - Prob. 7PCh. 6.4 - Prob. 8PCh. 6.4 - Prob. 9PCh. 6.4 - Prob. 10PCh. 6.4 - Prob. 11PCh. 6.4 - Prob. 12PCh. 6.4 - Prob. 13PCh. 6.5 - Prob. 1PCh. 6.5 - Find the duals of the following LPs: Ch. 6.5 - Prob. 3PCh. 6.5 - Prob. 4PCh. 6.5 - Prob. 5PCh. 6.5 - Prob. 6PCh. 6.6 - Prob. 1PCh. 6.6 - Prob. 2PCh. 6.7 - Prob. 1PCh. 6.7 - Prob. 2PCh. 6.7 - Prob. 3PCh. 6.7 - Prob. 4PCh. 6.7 - Prob. 5PCh. 6.7 - Prob. 6PCh. 6.7 - Prob. 7PCh. 6.7 - Prob. 8PCh. 6.7 - Prob. 9PCh. 6.8 - Prob. 1PCh. 6.8 - Prob. 2PCh. 6.8 - Prob. 3PCh. 6.8 - Prob. 4PCh. 6.8 - Prob. 5PCh. 6.8 - Prob. 6PCh. 6.8 - Prob. 8PCh. 6.8 - Prob. 9PCh. 6.8 - Prob. 10PCh. 6.8 - Prob. 11PCh. 6.9 - Prob. 1PCh. 6.9 - Prob. 2PCh. 6.9 - Prob. 3PCh. 6.10 - Prob. 1PCh. 6.10 - Prob. 2PCh. 6.10 - Prob. 3PCh. 6.11 - Prob. 1PCh. 6.11 - Prob. 3PCh. 6.11 - Prob. 4PCh. 6.12 - Prob. 5PCh. 6.12 - Prob. 6PCh. 6.12 - Prob. 7PCh. 6 - Prob. 1RPCh. 6 - Prob. 2RPCh. 6 - Prob. 3RPCh. 6 - Prob. 4RPCh. 6 - Prob. 5RPCh. 6 - Prob. 6RPCh. 6 - Prob. 7RPCh. 6 - Prob. 8RPCh. 6 - Prob. 9RPCh. 6 - Prob. 10RPCh. 6 - Prob. 11RPCh. 6 - Prob. 13RPCh. 6 - Prob. 14RPCh. 6 - Prob. 15RPCh. 6 - Prob. 17RPCh. 6 - Prob. 18RPCh. 6 - Prob. 19RPCh. 6 - Prob. 20RPCh. 6 - Prob. 21RPCh. 6 - Prob. 22RPCh. 6 - Prob. 25RPCh. 6 - Prob. 29RPCh. 6 - Prob. 33RPCh. 6 - Prob. 34RPCh. 6 - Prob. 35RPCh. 6 - Prob. 36RPCh. 6 - Prob. 37RP
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Operations Research : Applications and Algorithms
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