Introduction to Operations ResearchCD-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 150
... nonnegativity constraints , any problem containing variables allowed to be negative must be converted to an equivalent problem involving only nonnegative variables before the simplex method is applied . Fortunately , this conversion can ...
... nonnegativity constraints , any problem containing variables allowed to be negative must be converted to an equivalent problem involving only nonnegative variables before the simplex method is applied . Fortunately , this conversion can ...
Page 180
... nonnegativity constraint for x1 ) . ( a ) Reformulate this problem so all variables have nonnegativity constraints . ( a ) Reformulate this problem so that all variables have nonnega- tivity constraints . DI ( b ) Work through the ...
... nonnegativity constraint for x1 ) . ( a ) Reformulate this problem so all variables have nonnegativity constraints . ( a ) Reformulate this problem so that all variables have nonnega- tivity constraints . DI ( b ) Work through the ...
Page 289
... constraints yield dual variables without nonnegativity constraints ) by first converting the primal problem to our standard form ( see Table 6.12 ) , then constructing its dual problem , and next con- verting this dual problem to the ...
... constraints yield dual variables without nonnegativity constraints ) by first converting the primal problem to our standard form ( see Table 6.12 ) , then constructing its dual problem , and next con- verting this dual problem to 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 Courseware CPLEX decision variables dual problem dual simplex method dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal programming graphical identify increase initial BF solution integer 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 resource right-hand sides sensitivity analysis shadow prices shown slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero