Introduction to Operations ResearchCD-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 176
... problem . Maximize Z = 2x1 + 4x2 + 3x3 , subject to 3x1 + 4x2 + 2x3 ≤ 60 2x1 + x2 + 2x3 ≤40 x1 + 3x2 + 2x3 ≤ 80 and X2 ≥ 0 , X3 ... following constraints have been provided 176 4 SOLVING LINEAR PROGRAMMING PROBLEMS : THE SIMPLEX METHOD.
... problem . Maximize Z = 2x1 + 4x2 + 3x3 , subject to 3x1 + 4x2 + 2x3 ≤ 60 2x1 + x2 + 2x3 ≤40 x1 + 3x2 + 2x3 ≤ 80 and X2 ≥ 0 , X3 ... following constraints have been provided 176 4 SOLVING LINEAR PROGRAMMING PROBLEMS : THE SIMPLEX METHOD.
Page 179
... problem . 4.6-9 . Consider the following problem . Minimize Z = 2x1 + x2 + 3x3 , subject to 5x + 2x2 + 7x3 = 420 3x + 2x2 + 5x3 ≥ 280 I ( a ) Using the Big M method , work through the ... following statements as true CHAPTER 4 PROBLEMS 179.
... problem . 4.6-9 . Consider the following problem . Minimize Z = 2x1 + x2 + 3x3 , subject to 5x + 2x2 + 7x3 = 420 3x + 2x2 + 5x3 ≥ 280 I ( a ) Using the Big M method , work through the ... following statements as true CHAPTER 4 PROBLEMS 179.
Page 180
... following problem directly by hand . ( Do not use your OR Courseware . ) Minimize Z = 3x1 + 8x2 + 5x3 , subject to 3x2 + 4x370 3x1 + 5x2 + ... following problem . and Maximize 180 4 SOLVING LINEAR PROGRAMMING PROBLEMS : THE SIMPLEX METHOD.
... following problem directly by hand . ( Do not use your OR Courseware . ) Minimize Z = 3x1 + 8x2 + 5x3 , subject to 3x2 + 4x370 3x1 + 5x2 + ... following problem . and Maximize 180 4 SOLVING LINEAR PROGRAMMING PROBLEMS : THE SIMPLEX METHOD.
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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 allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost Courseware CPLEX decision variables described dual problem dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau flow following problem formulation functional constraints Gaussian elimination given graphical identify increase initial BF solution integer iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero