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The following LP formulation represents a transportation problem where raw material (in tons) is transported from Supplier i, i={1,2,3} to Plant j, j={1,2,3). The problem is solved and the optimal objective function value i 5200. Using the sensitivity report shown below, what is the dual variable of the demand constraint of Plan 3? Min Total cost = 1x11 + 3x12 + 5x13 +3.5x21 +4x22+4.8x23 +3.5x31 +3.6x32+3.2x33 Subject to x31+x32+x33 <=500 x11+x21+x31 = 500 x12+x22+x32 = 700 x13+x23+x33 = 600 xij<-200, for i= {2,3} &j= {1, 2, 3} xij >= 0, for i= {1,2,3} &j= {1, 2, 3) Final Reduced Objective Allowable Allowable Name Value Cost Coefficient Increase Decrease 500 0 1 2.5 1E+30 700 3 0.6 1E+30 200 0 5 0.2 1E+30 0 0 3.5 2.5 1E+30 0 4 1E+30 200 0 4.8 0.2 0 0 3.5 1E+30 0 0 3.6 1E+30 200 3.2 1.8 Variables X11 X12 X13 X21 X22 X23 X31 X32 X33 1 1E+30 2.5 0.6 1E+30

The following LP formulation represents a transportation problem where raw material (in tons) is transported from Supplier i, i={1,2,3} to Plant j, j={1,2,3). The problem is solved and the optimal objective function value i 5200. Using the sensitivity report shown below, what is the dual variable of the demand constraint of Plan 3? Min Total cost = 1x11 + 3x12 + 5x13 +3.5x21 +4x22+4.8x23 +3.5x31 +3.6x32+3.2x33 Subject to x31+x32+x33 <=500 x11+x21+x31 = 500 x12+x22+x32 = 700 x13+x23+x33 = 600 xij<-200, for i= {2,3} &j= {1, 2, 3} xij >= 0, for i= {1,2,3} &j= {1, 2, 3) Final Reduced Objective Allowable Allowable Name Value Cost Coefficient Increase Decrease 500 0 1 2.5 1E+30 700 3 0.6 1E+30 200 0 5 0.2 1E+30 0 0 3.5 2.5 1E+30 0 4 1E+30 200 0 4.8 0.2 0 0 3.5 1E+30 0 0 3.6 1E+30 200 3.2 1.8 Variables X11 X12 X13 X21 X22 X23 X31 X32 X33 1 1E+30 2.5 0.6 1E+30

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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The following LP formulation represents a transportation problem where raw material (in tons) is transported from Supplier i, i={1,2,3} to Plant j, j={1,2,3). The problem is solved and the optimal objective function value is 5200. Using the sensitivity report shown below, what is the dual variable of the demand constraint of Plant 3? Min Total cost = 1x11 + 3x12 + 5x13 +3.5x21+4x22+4.8x23 +3.5x31 +3.6x32+3.2x33 Subject to x31+x32+x33 < 500 x11+x21+x31 = 500 x12 + x22+x32 = 700 x13 + x23+x33 = 600 xij<=200, for i= (2, 3) &j= {1, 2, 3) xij = 0, for i= {1,2,3} &j= {1, 2, 3) Final Reduced Objective Allowable Allowable Name Value Cost Coefficient Increase Decrease 500 0 1 2.5 1E+30 700 0.6 1E+30 200 1E+30 0.2 0 1E+30 2.5 0 200 1E+30 0.2 1E+30 0 0 1E+30 200 1.8 Variables X11 X12 X13 X21 X22 X23 X31 X32 X33 0 0 0 0 0 0 0 0 3 3.5 4 4.8 3.5 3.6 3.2 1 1E+30 2.5 0.6 1E+30
Transcribed Image Text:The following LP formulation represents a transportation problem where raw material (in tons) is transported from Supplier i, i={1,2,3} to Plant j, j={1,2,3). The problem is solved and the optimal objective function value is 5200. Using the sensitivity report shown below, what is the dual variable of the demand constraint of Plant 3? Min Total cost = 1x11 + 3x12 + 5x13 +3.5x21+4x22+4.8x23 +3.5x31 +3.6x32+3.2x33 Subject to x31+x32+x33 < 500 x11+x21+x31 = 500 x12 + x22+x32 = 700 x13 + x23+x33 = 600 xij<=200, for i= (2, 3) &j= {1, 2, 3) xij = 0, for i= {1,2,3} &j= {1, 2, 3) Final Reduced Objective Allowable Allowable Name Value Cost Coefficient Increase Decrease 500 0 1 2.5 1E+30 700 0.6 1E+30 200 1E+30 0.2 0 1E+30 2.5 0 200 1E+30 0.2 1E+30 0 0 1E+30 200 1.8 Variables X11 X12 X13 X21 X22 X23 X31 X32 X33 0 0 0 0 0 0 0 0 3 3.5 4 4.8 3.5 3.6 3.2 1 1E+30 2.5 0.6 1E+30
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