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 86
Page 32
A feasible solution is a solution for which all the constraints are satisfied . An infeasible solution is a solution for which at least one constraint is violated . In the example , the points ( 2 , 3 ) and ( 4 , 1 ) in Fig .
A feasible solution is a solution for which all the constraints are satisfied . An infeasible solution is a solution for which at least one constraint is violated . In the example , the points ( 2 , 3 ) and ( 4 , 1 ) in Fig .
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 x1 = 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 x1 = 3 , x2 = 3 ...
Page 246
No Yes Feasible ? Yes No Optimal Superoptimal Suboptimal Neither feasible nor 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 ...
No Yes Feasible ? Yes No Optimal Superoptimal Suboptimal Neither feasible nor 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 ...
What people are saying - Write a review
Reviews aren't verified, but Google checks for and removes fake content when it's identified
User Review - Flag as inappropriate
i
User Review - Flag as inappropriate
I want review this book
Other editions - View all
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 |