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
Results 1-3 of 85
Page 35
... optimal , each with Z = 18 . 0 2 4 6 8 10 XI on the line segment connecting ( 2 , 6 ) and ( 4 , 3 ) would be optimal ... solution . If the problem has multiple optimal solutions , at least two must be CPF solutions . ( 4 , ∞ ) , Z ...
... optimal , each with Z = 18 . 0 2 4 6 8 10 XI on the line segment connecting ( 2 , 6 ) and ( 4 , 3 ) would be optimal ... solution . If the problem has multiple optimal solutions , at least two must be CPF solutions . ( 4 , ∞ ) , Z ...
Page 223
... feasible solution is optimal , it must be a CPF solution . ( b ) The number of CPF solutions is at least ( m + n ) ! m ! n ! ( c ) If a CPF solution has adjacent CPF solutions that are better ( as measured by Z ) , then one of these ...
... feasible solution is optimal , it must be a CPF solution . ( b ) The number of CPF solutions is at least ( m + n ) ! m ! n ! ( c ) If a CPF solution has adjacent CPF solutions that are better ( as measured by Z ) , then one of these ...
Page 397
... optimal solution . D , I ( d ) Use Vogel's approximation method to obtain an initial BF solution for this problem . DI ( e ) Starting with the initial BF solution from part ( d ) , interac- tively apply the transportation simplex method ...
... optimal solution . D , I ( d ) Use Vogel's approximation method to obtain an initial BF solution for this problem . DI ( e ) Starting with the initial BF solution from part ( d ) , interac- tively apply the transportation simplex method ...
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