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 60
The cost per unit shipped through each shipping lane is shown next to the arrow . Also shown next to F1 F2 and DC → W2 are the maximum amounts that can be shipped through these lanes . The other lanes have sufficient shipping capacity ...
The cost per unit shipped through each shipping lane is shown next to the arrow . Also shown next to F1 F2 and DC → W2 are the maximum amounts that can be shipped through these lanes . The other lanes have sufficient shipping capacity ...
Page 91
Management wants to determine how many units of each product to produce so as to maximize profit . For each unit of product 1 , 1 unit of frame parts and 2 units of electrical components are required . For each unit of product 2 ...
Management wants to determine how many units of each product to produce so as to maximize profit . For each unit of product 1 , 1 unit of frame parts and 2 units of electrical components are required . For each unit of product 2 ...
Page 992
Regular - Time Unit Cost Month Requirement Sarah purchases the circus peanuts from Peter's Peanut Shop . She has been purchasing 100 bags at a time . However , to encourage larger purchases , Peter now is offering her discounts for ...
Regular - Time Unit Cost Month Requirement Sarah purchases the circus peanuts from Peter's Peanut Shop . She has been purchasing 100 bags at a time . However , to encourage larger purchases , Peter now is offering her discounts for ...
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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