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 222
( c ) Develop the corresponding table for the corner - point infeasi- ble solutions , etc. Also identify the sets of defining equations and nonbasic variables that do not yield a solution . 5.1-4 . Consider the following problem .
( c ) Develop the corresponding table for the corner - point infeasi- ble solutions , etc. Also identify the sets of defining equations and nonbasic variables that do not yield a solution . 5.1-4 . Consider the following problem .
Page 249
constructing the dual problem except that the nonnegativity constraint for the corresponding dual variable should be deleted ( i.e. , this variable is unconstrained in sign ) . By the symme- try property , deleting a nonnegativity ...
constructing the dual problem except that the nonnegativity constraint for the corresponding dual variable should be deleted ( i.e. , this variable is unconstrained in sign ) . By the symme- try property , deleting a nonnegativity ...
Page 252
With the Big M method , since M has been added initially to the coefficient of each artificial variable in row 0 , the current value of each corresponding dual variable is the current co- efficient of this artificial variable minus M.
With the Big M method , since M has been added initially to the coefficient of each artificial variable in row 0 , the current value of each corresponding dual variable is the current co- efficient of this artificial variable minus M.
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity additional algorithm allowable amount apply assigned basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider Construct corresponding cost CPF solution decision variables described determine developed dual problem entering equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming linear programming model Maximize million Minimize month needed node objective function obtained operations optimal optimal solution original parameters path perform plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised sensitivity analysis shown shows side simplex method simplex tableau slack solve step Table tableau tion unit values weeks Wyndor Glass x₁ zero