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 539
In general , the states are the various possible conditions in which the system
might be at that stage of the problem . The number of states may be either finite (
as in the stagecoach problem ) or infinite ( as in some subsequent examples ) ...
In general , the states are the various possible conditions in which the system
might be at that stage of the problem . The number of states may be either finite (
as in the stagecoach problem ) or infinite ( as in some subsequent examples ) ...
Page 556
We now have an infinite number of possible states ( 240 SS3 = 255 ) , so it is no
longer feasible to solve separately for x for each possible value of sz . Therefore ,
we instead have solved for x as a function of the unknown Sz . Using $ } ( s ) = f ...
We now have an infinite number of possible states ( 240 SS3 = 255 ) , so it is no
longer feasible to solve separately for x for each possible value of sz . Therefore ,
we instead have solved for x as a function of the unknown Sz . Using $ } ( s ) = f ...
Page 560
From a theoretical standpoint , this difference is not particularly serious . It only
means that , instead of considering all possible values of the one state variable ,
we must consider all possible combinations of values of the several state
variables ...
From a theoretical standpoint , this difference is not particularly serious . It only
means that , instead of considering all possible values of the one state variable ,
we must consider all possible combinations of values of the several state
variables ...
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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