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 318
The upper bound technique avoids this increased effort by removing the upper
bound constraints from the functional constraints and treating them separately ,
essentially like nonnegativity constraints . Removing the upper bound constraints
in ...
The upper bound technique avoids this increased effort by removing the upper
bound constraints from the functional constraints and treating them separately ,
essentially like nonnegativity constraints . Removing the upper bound constraints
in ...
Page 320
4 Equations and calculations for the initial leaving basic variable in the example
for the upper bound technique Initial Set of Equations Maximum Feasible Value
of xy ( 0 ) Z - 2x1 = 20 54 ( since un = 4 ) ( 1 ) 4x1 + x2 = 12 xus 12 = 3 ( 2 ) – 2x1
+ ...
4 Equations and calculations for the initial leaving basic variable in the example
for the upper bound technique Initial Set of Equations Maximum Feasible Value
of xy ( 0 ) Z - 2x1 = 20 54 ( since un = 4 ) ( 1 ) 4x1 + x2 = 12 xus 12 = 3 ( 2 ) – 2x1
+ ...
Page 614
In general terms , two features are sought in choosing a relaxation : it can be
solved relatively quickly , and provides a relatively tight bound . Neither alone is
adequate . The LP relaxation is popular because it provides an excellent trade -
off ...
In general terms , two features are sought in choosing a relaxation : it can be
solved relatively quickly , and provides a relatively tight bound . Neither alone is
adequate . The LP relaxation is popular because it provides an excellent trade -
off ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
57 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 calculations called capacity changes coefficients column complete Consider constraints construct corresponding cost CPF solution demand described determine direction distribution dual problem entering equal equations estimates example feasible FIGURE final flow problem Formulate 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 resource respective resulting revised Select 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 |