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 120
As indicated next , we call x2 the entering basic variable for iteration 1 . At any
iteration of the simplex method , the purpose of step 1 is to choose one nonbasic
variable to increase from zero ( while the values of the basic variables are
adjusted ...
As indicated next , we call x2 the entering basic variable for iteration 1 . At any
iteration of the simplex method , the purpose of step 1 is to choose one nonbasic
variable to increase from zero ( while the values of the basic variables are
adjusted ...
Page 178
Also identify the initial entering basic variable and the leaving basic variable . 1 (
e ) Work through the simplex method step by step to solve the problem . ( a )
Solve this problem graphically . ( b ) Using the Big M method , construct the
complete ...
Also identify the initial entering basic variable and the leaving basic variable . 1 (
e ) Work through the simplex method step by step to solve the problem . ( a )
Solve this problem graphically . ( b ) Using the Big M method , construct the
complete ...
Page 377
Step 2 . Increasing the entering basic variable from zero sets off a chain reaction
of compensating changes in other basic variables ( allocations ) , in order to
continue satisfying the supply and demand constraints . The first basic variable to
be ...
Step 2 . Increasing the entering basic variable from zero sets off a chain reaction
of compensating changes in other basic variables ( allocations ) , in order to
continue satisfying the supply and demand constraints . The first basic variable to
be ...
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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