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 298
C ( a ) Suppose that the estimates for C , and c2 are correct but the estimates for
both b , and b2 are incorrect . Consider the following four cases where the true
values of b , and b2 differ from their estimates by the same percentage : ( 1 ) both
b ...
C ( a ) Suppose that the estimates for C , and c2 are correct but the estimates for
both b , and b2 are incorrect . Consider the following four cases where the true
values of b , and b2 differ from their estimates by the same percentage : ( 1 ) both
b ...
Page 487
Intuitively , this formula is placing most of the weight on the most likely estimate
and then small equal weights on the other two estimates . MS Project provides
the option of calculating u for each activity with this formula . Choosing Table : PA
_ ...
Intuitively , this formula is placing most of the weight on the most likely estimate
and then small equal weights on the other two estimates . MS Project provides
the option of calculating u for each activity with this formula . Choosing Table : PA
_ ...
Page 517
Using the PERT three - estimate approach , the three estimates for one of the
activities are as follows : optimistic estimate = 30 days , most likely estimate = 36
days , pessimistic estimate = 48 days . What are the resulting estimates of the
mean ...
Using the PERT three - estimate approach , the three estimates for one of the
activities are as follows : optimistic estimate = 30 days , most likely estimate = 36
days , pessimistic estimate = 48 days . What are the resulting estimates of the
mean ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
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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