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. |
From inside the book
Results 1-3 of 79
Page 60
... unit shipped through each shipping lane is shown next to the arrow . Also shown next to F1 → F2 and DC → W2 are ... unit $ 200 / unit 10 units max . 40 units produced 2 F2 $ 300 / unit $ 900 / unit WI 30 units needed DC $ 200 / unit ...
... unit shipped through each shipping lane is shown next to the arrow . Also shown next to F1 → F2 and DC → W2 are ... unit $ 200 / unit 10 units max . 40 units produced 2 F2 $ 300 / unit $ 900 / unit WI 30 units needed DC $ 200 / unit ...
Page 715
... units of Product 1. For the first 20 units pro- duced of Product 2 , the unit profit is estimated at $ 240 . The unit profit would be $ 120 for each of the next 20 units and $ 90 for any additional units . For the first 10 units of Product ...
... units of Product 1. For the first 20 units pro- duced of Product 2 , the unit profit is estimated at $ 240 . The unit profit would be $ 120 for each of the next 20 units and $ 90 for any additional units . For the first 10 units of Product ...
Page 947
... unit time for the speaker example with quantity discounts . 90,000 85,000 82,500 10,000 25,000 80,000 T1 ( unit cost equals $ 11 ) T2 ( unit cost equals $ 10 ) T3 ( unit cost equals $ 9.50 ) Batch size Q ( If h were not independent of the ...
... unit time for the speaker example with quantity discounts . 90,000 85,000 82,500 10,000 25,000 80,000 T1 ( unit cost equals $ 11 ) T2 ( unit cost equals $ 10 ) T3 ( unit cost equals $ 9.50 ) Batch size Q ( If h were not independent of the ...
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 CPF solution CPLEX decision variables described 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 graphical identify increase initial BF solution integer interior-point 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 right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero