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 34
Page 333
... programming , there is a hierarchy of priority levels for the goals , so that the goals of primary importance receive first- priority attention , those of ... goal programming 7.5 LINEAR GOAL PROGRAMMING AND ITS SOLUTION PROCEDURES 333.
... programming , there is a hierarchy of priority levels for the goals , so that the goals of primary importance receive first- priority attention , those of ... goal programming 7.5 LINEAR GOAL PROGRAMMING AND ITS SOLUTION PROCEDURES 333.
Page 335
... programming model . ( Because there is no penalty for exceeding the profit goal of 125 or being under the investment goal of 55 , neither y1 nor y3 should appear in this objective function representing the total penalty for deviations ...
... programming model . ( Because there is no penalty for exceeding the profit goal of 125 or being under the investment goal of 55 , neither y1 nor y3 should appear in this objective function representing the total penalty for deviations ...
Page 346
... goal were to be increased to wanting at least $ 140 million ( without any change in the original penalty weights ) ... programming model for this problem . ( b ) Reformulate this model as a linear programming model . c ( c ) Use the ...
... goal were to be increased to wanting at least $ 140 million ( without any change in the original penalty weights ) ... programming model for this problem . ( b ) Reformulate this model as a linear programming model . c ( c ) Use the ...
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