Introduction to Operations Research, Volume 1CD-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 73
3.1 and 3.4 , the model sizes range from three functional constraints and two decision variables ( for the Wyndor and radiation therapy problems ) up to 17 functional constraints and 12 decision variables ( for the Save - It Company ...
3.1 and 3.4 , the model sizes range from three functional constraints and two decision variables ( for the Wyndor and radiation therapy problems ) up to 17 functional constraints and 12 decision variables ( for the Save - It Company ...
Page 75
When maximizing this objective function , the 21,000 decision variables need to satisfy nonnegativity constraints as well as four types of functional constraints — production capacity constraints , plant balance constraints ( equality ...
When maximizing this objective function , the 21,000 decision variables need to satisfy nonnegativity constraints as well as four types of functional constraints — production capacity constraints , plant balance constraints ( equality ...
Page 249
Another shortcut involves functional constraints in > form for a maximization problem . The straightforward ( but longer ) approach would begin by converting each such constraint to s form n 0 ;; X ; = b ; - - di ; X ; < -bi . a ...
Another shortcut involves functional constraints in > form for a maximization problem . The straightforward ( but longer ) approach would begin by converting each such constraint to s form n 0 ;; X ; = b ; - - di ; X ; < -bi . a ...
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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 assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution decision variables demand described determine direction distribution dual problem entering equal equations estimates example feasible feasible region FIGURE final flow formulation 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 remaining resource respective resulting shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit weeks Wyndor Glass zero