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 158
Adjustable Cells Cell Name Value Final Reduced Objective Allowable Allowable Cost Coefficient Increase Decrease $ C $ 9 Solution Doors 2 0 3 $ D $ 9 Solution Windows 6 0 5 4.5 1E + 30 3 3 Constraints Final Shadow Constraint Allowable ...
Adjustable Cells Cell Name Value Final Reduced Objective Allowable Allowable Cost Coefficient Increase Decrease $ C $ 9 Solution Doors 2 0 3 $ D $ 9 Solution Windows 6 0 5 4.5 1E + 30 3 3 Constraints Final Shadow Constraint Allowable ...
Page 266
4.7 , this range of values for b2 is referred to as its allowable range to stay feasible . For any b1 , recall from Sec . 4.7 that its allowable range to stay feasible is the range of values over which the current optimal BF solution ...
4.7 , this range of values for b2 is referred to as its allowable range to stay feasible . For any b1 , recall from Sec . 4.7 that its allowable range to stay feasible is the range of values over which the current optimal BF solution ...
Page 272
Since z * z = y * A , this immediately yields the same allowable range . Figure 6.3 provides graphical insight into why c1 ≤7 is the allowable range . At C1 c1 = 7 , the objective function becomes Z = 7.5x1 + 5x2 = 2.5 ( 3x1 + 2x2 ) ...
Since z * z = y * A , this immediately yields the same allowable range . Figure 6.3 provides graphical insight into why c1 ≤7 is the allowable range . At C1 c1 = 7 , the objective function becomes Z = 7.5x1 + 5x2 = 2.5 ( 3x1 + 2x2 ) ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity additional algorithm allowable amount apply assigned basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider Construct corresponding cost CPF solution decision variables described determine developed dual problem entering equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming linear programming model Maximize million Minimize month needed node objective function obtained operations optimal optimal solution original parameters path perform plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised sensitivity analysis shown shows side simplex method simplex tableau slack solve step Table tableau tion unit values weeks Wyndor Glass x₁ zero
Bibliographic information
| Title | Introduction to Operations Research McGraw-Hill International Editions 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 | Pennsylvania State University |
| Digitized | 26 Aug 2009 |
| ISBN | 0071181636, 9780071181631 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |