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. |
From inside the book
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Page 148
... Big M and two - phase methods . Begin with their ob- jective functions . Big M Method : Minimize Z = 0.4x1 + 0.5x2 + MX4 + MX6 . Two - Phase Method : Phase 1 : Phase 2 : Minimize Minimize Z = X4 + X6 . = Z 0.4x0.5x2 . Because the MX4 ...
... Big M and two - phase methods . Begin with their ob- jective functions . Big M Method : Minimize Z = 0.4x1 + 0.5x2 + MX4 + MX6 . Two - Phase Method : Phase 1 : Phase 2 : Minimize Minimize Z = X4 + X6 . = Z 0.4x0.5x2 . Because the MX4 ...
Page 149
... method from proceeding as usual and ultimately re- porting a supposedly optimal solution . Fortunately , the ... Big M method or phase 1 of the two - phase method yields a final solution that has at least one artificial variable greater ...
... method from proceeding as usual and ultimately re- porting a supposedly optimal solution . Fortunately , the ... Big M method or phase 1 of the two - phase method yields a final solution that has at least one artificial variable greater ...
Page 178
... Big M method , construct the complete first simplex tableau for the simplex method and identify the corresponding initial ( artificial ) BF solution . Also identify the initial entering basic variable and the leaving basic variable . 1 ...
... Big M method , construct the complete first simplex tableau for the simplex method and identify the corresponding initial ( artificial ) BF solution . Also identify the initial entering basic variable and the leaving basic variable . 1 ...
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 allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost CPF solution CPLEX decision variables described 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 graphical identify increase initial BF solution integer interior-point 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 right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero
Bibliographic information
| Title | Introduction to Operations Research, Volume 1 Introduction to Operations Research, Frederick S. Hillier McGraw-Hill industrial & plant engineering series McGraw-Hill series in industrial engineering and management science |
| Authors | Frederick S. Hillier, Gerald J. Lieberman |
| Edition | 7, illustrated |
| Publisher | McGraw-Hill, 2001 |
| Original from | the University of Michigan |
| Digitized | 8 Aug 2011 |
| ISBN | 0072321695, 9780072321692 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |