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 318
... bound technique avoids this increased effort by removing the upper bound constraints from the functional constraints and treating them separately , essentially like nonnegativity constraints . Removing the upper bound constraints in ...
... bound technique avoids this increased effort by removing the upper bound constraints from the functional constraints and treating them separately , essentially like nonnegativity constraints . Removing the upper bound constraints in ...
Page 615
... bound tech- nique can be used to find a nearly optimal solution , generally with much less computa- tional effort ... bound such that Z ** < bound so that either Bound K≤ Z * or ( 1 - a ) bound ≤ Z * would imply that the corresponding ...
... bound tech- nique can be used to find a nearly optimal solution , generally with much less computa- tional effort ... bound such that Z ** < bound so that either Bound K≤ Z * or ( 1 - a ) bound ≤ Z * would imply that the corresponding ...
Page 640
... bound algorithm for sequencing prob- lems of this type by specifying how the branch , bound , and fathoming steps would be performed . ( b ) Use this algorithm to solve this problem . 12.6-9 . * Consider the following nonlinear BIP ...
... bound algorithm for sequencing prob- lems of this type by specifying how the branch , bound , and fathoming steps would be performed . ( b ) Use this algorithm to solve this problem . 12.6-9 . * Consider the following nonlinear BIP ...
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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 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