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. |
From inside the book
Results 1-3 of 79
Page 613
... algorithm . Also included in the OR Courseware is an interactive routine for executing this algorithm . As usual , the Excel , LINGO / LINDO , and MPL / CPLEX files for this chapter in your OR Courseware show how the student version of ...
... algorithm . Also included in the OR Courseware is an interactive routine for executing this algorithm . As usual , the Excel , LINGO / LINDO , and MPL / CPLEX files for this chapter in your OR Courseware show how the student version of ...
Page 698
... algorithm , we present here the Frank- Wolfe algorithm ' for the case of linearly constrained convex programming ( so the con- straints are Ax ≤ b and x = 0 in matrix form ) . This procedure is particularly straightfor- ward ; it ...
... algorithm , we present here the Frank- Wolfe algorithm ' for the case of linearly constrained convex programming ( so the con- straints are Ax ≤ b and x = 0 in matrix form ) . This procedure is particularly straightfor- ward ; it ...
Page 718
... algorithm . DI 13.9-5 . Consider the quadratic programming example presented in Sec . 13.7 . Starting from the initial trial solution ( x1 , x2 ) = ( 5 , 5 ) , apply seven iterations of the Frank - Wolfe algorithm . 13.9-6 . Reconsider ...
... algorithm . DI 13.9-5 . Consider the quadratic programming example presented in Sec . 13.7 . Starting from the initial trial solution ( x1 , x2 ) = ( 5 , 5 ) , apply seven iterations of the Frank - Wolfe algorithm . 13.9-6 . Reconsider ...
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