Introduction to Operations Research, Volume 1CD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 217
TABLE 5.10 General notation for initial and final simplex tableaux in matrix form , Initial Tableau Row 0 : illustrated by the Wyndor Glass Co. problem t = [ -3 , -5 0 , 0 , 0¦ 0 ] = [ −c 0 0 ] . 1 0 1 0 0 41 Other rows : T = 0 20 1 0 ...
TABLE 5.10 General notation for initial and final simplex tableaux in matrix form , Initial Tableau Row 0 : illustrated by the Wyndor Glass Co. problem t = [ -3 , -5 0 , 0 , 0¦ 0 ] = [ −c 0 0 ] . 1 0 1 0 0 41 Other rows : T = 0 20 1 0 ...
Page 388
TABLE 8.28 Parameter table for the transportation problem formulation of Option 1 for the Better Products Co. problem Cost per Unit Distributed Destination ( Product ) Source ( Plant ) Demand 123 1 2 3 4 5 ( D ) Supply 41 27 28 40 29 M ...
TABLE 8.28 Parameter table for the transportation problem formulation of Option 1 for the Better Products Co. problem Cost per Unit Distributed Destination ( Product ) Source ( Plant ) Demand 123 1 2 3 4 5 ( D ) Supply 41 27 28 40 29 M ...
Page 389
TABLE 8.28 Parameter table for the transportation problem formulation of Option 1 for the Better Products Co. problem Cost per Unit Distributed Destination ( Product ) Source ( Plant ) Demand 1 2 3 4 5 ( D ) Supply 123 41 27 28 24 0 75 ...
TABLE 8.28 Parameter table for the transportation problem formulation of Option 1 for the Better Products Co. problem Cost per Unit Distributed Destination ( Product ) Source ( Plant ) Demand 1 2 3 4 5 ( D ) Supply 123 41 27 28 24 0 75 ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero