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 289
( b ) Construct the dual problem . ( c ) Demonstrate graphically that the dual
problem has no feasible solutions . 6 . 4 - 5 . Consider the two versions of the
dual problem for the radiation therapy example that are given in Tables 6 . 15
and 6 . 16 .
( b ) Construct the dual problem . ( c ) Demonstrate graphically that the dual
problem has no feasible solutions . 6 . 4 - 5 . Consider the two versions of the
dual problem for the radiation therapy example that are given in Tables 6 . 15
and 6 . 16 .
Page 574
Consider the following nonlinear programming problem . Minimize Z = x1 + 2xž
subject to x + xż z 2 . ( There are no nonnegativity constraints . ) Use dynamic
program - ming to solve this problem . X , 30 , X220 . Use dynamic programming
to ...
Consider the following nonlinear programming problem . Minimize Z = x1 + 2xž
subject to x + xż z 2 . ( There are no nonnegativity constraints . ) Use dynamic
program - ming to solve this problem . X , 30 , X220 . Use dynamic programming
to ...
Page 709
Consider the following function : f ( x ) = 5xy + 2x3 + x3 - 3xx + 4x + 2x + x +
3x5X6 + 6xś + 3x6x7 + x3 . Show that f ( x ) is convex by expressing it as a sum of
functions of one or two variables and then showing ( see Appendix ...
Consider the following function : f ( x ) = 5xy + 2x3 + x3 - 3xx + 4x + 2x + x +
3x5X6 + 6xś + 3x6x7 + x3 . Show that f ( x ) is convex by expressing it as a sum of
functions of one or two variables and then showing ( see Appendix ...
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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 |