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 119
Choose x , and x2 to be the nonbasic variables ( = 0 ) for the initial BF solution : (
0 , 0 , 4 , 12 , 18 ) . Not optimal , because increasing either nonbasic variable ( x ,
or x2 ) increases Z . Optimality test Iteration 1 Step 1 Not optimal , because ...
Choose x , and x2 to be the nonbasic variables ( = 0 ) for the initial BF solution : (
0 , 0 , 4 , 12 , 18 ) . Not optimal , because increasing either nonbasic variable ( x ,
or x2 ) increases Z . Optimality test Iteration 1 Step 1 Not optimal , because ...
Page 199
Each such indicating variable is called a nonbasic variable for the corresponding
basic solution . The resulting conclusions and terminology ( already introduced in
Sec . 4 . 2 ) are summarized next . Each basic solution has m basic variables ...
Each such indicating variable is called a nonbasic variable for the corresponding
basic solution . The resulting conclusions and terminology ( already introduced in
Sec . 4 . 2 ) are summarized next . Each basic solution has m basic variables ...
Page 200
A BF solution is a basic solution where all m basic variables are nonnegative ( 20
) . A BF solution is said to be degenerate if any of these m variables equals zero .
Thus , it is possible for a variable to be zero and still not be a nonbasic variable ...
A BF solution is a basic solution where all m basic variables are nonnegative ( 20
) . A BF solution is said to be degenerate if any of these m variables equals zero .
Thus , it is possible for a variable to be zero and still not be a nonbasic variable ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
59 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 constraints Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible 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 nonnegative 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 transportation 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 |