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 236
Weak duality property : If x is a feasible solution for the primal problem and y is a feasible solution for the dual problem , then cx < yb . For example , for the Wyndor Glass Co. problem , one feasible solution is xy = 3 , x2 = 3 ...
Weak duality property : If x is a feasible solution for the primal problem and y is a feasible solution for the dual problem , then cx < yb . For example , for the Wyndor Glass Co. problem , one feasible solution is xy = 3 , x2 = 3 ...
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Yes No Yes Optimal Feasible ? Suboptimal Neither feasible nor superoptimal No Superoptimal To review the reasoning behind this property , note that the dual solution ( y * , z * – c ) must be feasible for the dual problem because the ...
Yes No Yes Optimal Feasible ? Suboptimal Neither feasible nor superoptimal No Superoptimal To review the reasoning behind this property , note that the dual solution ( y * , z * – c ) must be feasible for the dual problem because the ...
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to achieve dual feasibility as well ( the optimality test for the simplex method ) . By contrast , the dual simplex method deals with basic solutions in the primal problem that are dual feasible but not primal feasible .
to achieve dual feasibility as well ( the optimality test for the simplex method ) . By contrast , the dual simplex method deals with basic solutions in the primal problem that are dual feasible but not primal feasible .
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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 allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero
Bibliographic information
| Title | Introduction to Operations Research, Volume 1 Introduction to Operations Research, Frederick S. Hillier McGraw-Hill industrial & plant engineering series McGraw-Hill series in industrial engineering and management science |
| Authors | Frederick S. Hillier, Gerald J. Lieberman |
| Edition | 7, illustrated |
| Publisher | McGraw-Hill, 2001 |
| Original from | the University of Michigan |
| Digitized | 8 Aug 2011 |
| ISBN | 0072321695, 9780072321692 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |