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 333
... goal sets an upper limit that we do not want to exceed ( but falling under the limit is fine ) . 3. A two - sided goal sets a specific target that we do ... goal programming 7.5 LINEAR GOAL PROGRAMMING AND ITS SOLUTION PROCEDURES 333.
... goal sets an upper limit that we do not want to exceed ( but falling under the limit is fine ) . 3. A two - sided goal sets a specific target that we do ... 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 ...
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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 corresponding cost Courseware CPF solution CPLEX decision variables 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 interior-point iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize subject 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 simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero