## 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 369

To begin , all source rows and destination

To begin , all source rows and destination

**columns**of the transportation simplex tableau are initially under ... Eliminate that row or**column**( whichever had the smaller remaining supply or demand ) from further consideration .Page 371

At each iteration , after the difference for every row and

At each iteration , after the difference for every row and

**column**remaining under consideration is calculated and displayed , the largest difference is circled and the smallest unit cost in its row or**column**is enclosed in a box .Page 413

Now let us relate these

Now let us relate these

**columns**directly to the outline given for the algorithm . The input for nth iteration is provided by the fifth and sixth**columns**for the preceding iterations , where the solved nodes in the fifth**column**are then ...### What people are saying - Write a review

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### Other editions - View all

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