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 159
... gives the value of each constraint's left - hand side for the optimal solution . The next two columns give the shadow price and the current value of the right - hand side ( b ; ) for each constraint . When just one b ; value is then ...
... gives the value of each constraint's left - hand side for the optimal solution . The next two columns give the shadow price and the current value of the right - hand side ( b ; ) for each constraint . When just one b ; value is then ...
Page 170
... gives the difference between the two sides of each constraint . The Dual Prices column gives , by another name , the shadow prices discussed in Sec . 4.7 for these constraints . ' ( This alternate name comes from the fact found in Sec ...
... gives the difference between the two sides of each constraint . The Dual Prices column gives , by another name , the shadow prices discussed in Sec . 4.7 for these constraints . ' ( This alternate name comes from the fact found in Sec ...
Page 231
... gives the coefficients of a single variable in the respective constraints and then in the objective function , whereas each row ( except the bottom one ) gives the param- eters for a single contraint . For the dual problem , each row ...
... gives the coefficients of a single variable in the respective constraints and then in the objective function , whereas each row ( except the bottom one ) gives the param- eters for a single contraint . For the dual problem , each row ...
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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