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 173
( h ) For each CPF solution , identify the pair of constraint bound- The objective is to maximize the total profit from the two activiary equations that it satisfies . ties . The unit profit for activity 1 is $ 1,000 and the unit profit ...
( h ) For each CPF solution , identify the pair of constraint bound- The objective is to maximize the total profit from the two activiary equations that it satisfies . ties . The unit profit for activity 1 is $ 1,000 and the unit profit ...
Page 573
Maximize Z = xzxzx } , Parallel Units Component 1 Component 2 Component 3 Component 4 subject to 1 2 3 0.5 0.6 0.8 0.6 0.7 0.8 0.7 0.8 0.9 0.5 0.7 0.9 xy + 2x2 + 3x3 = 10 X2 21 , x = 1 , xz 21 , The probability that the system will ...
Maximize Z = xzxzx } , Parallel Units Component 1 Component 2 Component 3 Component 4 subject to 1 2 3 0.5 0.6 0.8 0.6 0.7 0.8 0.7 0.8 0.9 0.5 0.7 0.9 xy + 2x2 + 3x3 = 10 X2 21 , x = 1 , xz 21 , The probability that the system will ...
Page 574
Maximize Z = 5x1 + x2 , 11.3-19 . Consider the following nonlinear programming problem . Maximize Z = xixa , subject to 2x1 + x2 13 x } + x2 5 9 and x = 0 , x2 = 0 . subject to x } + x2 < 2 . ( There are no nonnegativity constraints . ) ...
Maximize Z = 5x1 + x2 , 11.3-19 . Consider the following nonlinear programming problem . Maximize Z = xixa , subject to 2x1 + x2 13 x } + x2 5 9 and x = 0 , x2 = 0 . subject to x } + x2 < 2 . ( There are no nonnegativity constraints . ) ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
SUPPLEMENT TO CHAPTER | 18 |
Copyright | |
52 other sections not shown
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Common terms and phrases
activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraint Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal 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 Maximize million Minimize month needed node nonbasic variables objective function obtained operations optimal optimal solution original parameters path plant possible presented primal problem Prob procedure profit programming problem provides range remaining resource respective resulting revised shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass 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 |