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 225
You are given the facts that the basic variables in the optimal so - lution are X3 ,
X1 , and xs and that 53 1 07 - 1 [ 11 - 3 17 2 4 1 = 7 - 6 9 - 3 . LO 1 3 1 2 - 3 10 ( a
) Use the given information to identify the optimal solution . ( b ) Use the given ...
You are given the facts that the basic variables in the optimal so - lution are X3 ,
X1 , and xs and that 53 1 07 - 1 [ 11 - 3 17 2 4 1 = 7 - 6 9 - 3 . LO 1 3 1 2 - 3 10 ( a
) Use the given information to identify the optimal solution . ( b ) Use the given ...
Page 786
T ( i ) Given that research is done , what is the expected payoff when using Bayes
' decision rule ? ( j ) Use the preceding results to determine the optimal policy
regarding whether to do the research and the choice of the decision alternative .
T ( i ) Given that research is done , what is the expected payoff when using Bayes
' decision rule ? ( j ) Use the preceding results to determine the optimal policy
regarding whether to do the research and the choice of the decision alternative .
Page 1187
667 lose and lose lose , given lose ( f , g ) Leland University should hire William .
If he predicts a winning season then they should hold the campaign . If he
predicts a losing season then they should not hold the campaign . 15 . 4 - 10 .
667 lose and lose lose , given lose ( f , g ) Leland University should hire William .
If he predicts a winning season then they should hold the campaign . If he
predicts a losing season then they should not hold the campaign . 15 . 4 - 10 .
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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 |