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 192
This situation is summarized in Table 5.1 , where defining equations refer to the constraint boundary equations that yield ( define ) the indicated CPF solution . For any linear programming problem with n decision variables , each CPF ...
This situation is summarized in Table 5.1 , where defining equations refer to the constraint boundary equations that yield ( define ) the indicated CPF solution . For any linear programming problem with n decision variables , each CPF ...
Page 199
The key ques- tion is : How do we tell whether a particular constraint boundary equation is one of the defining ... The values of the basic variables are given by the simultaneous solu- tion of the system of m equations for the problem ...
The key ques- tion is : How do we tell whether a particular constraint boundary equation is one of the defining ... The values of the basic variables are given by the simultaneous solu- tion of the system of m equations for the problem ...
Page 850
The equation expressing this principle is called the balance equation for state n . Af- ter constructing the balance equations for all the states in terms of the unknown P , prob- abilities , we can solve this system of equations ( plus ...
The equation expressing this principle is called the balance equation for state n . Af- ter constructing the balance equations for all the states in terms of the unknown P , prob- abilities , we can solve this system of equations ( plus ...
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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