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 81
A3.1 shows how this problem would be formulated with LINGO . The first line of this formulation is just a comment describing the model . Note that the comment is preceded by an exclamation point and ended by a semicolon .
A3.1 shows how this problem would be formulated with LINGO . The first line of this formulation is just a comment describing the model . Note that the comment is preceded by an exclamation point and ended by a semicolon .
Page 183
the lists of materials requirements for each pattern , and the lists of demand forecasts for each pattern determined by customer surveys at fashion shows . She remembers the hectic and sometimes nightmarish days of designing the fall ...
the lists of materials requirements for each pattern , and the lists of demand forecasts for each pattern determined by customer surveys at fashion shows . She remembers the hectic and sometimes nightmarish days of designing the fall ...
Page 454
( a ) Draw a rough map that shows the location of Texago's oil fields , refineries , and distribution centers . Add arrows to show the flow of crude oil and then petroleum products through this distribution network .
( a ) Draw a rough map that shows the location of Texago's oil fields , refineries , and distribution centers . Add arrows to show the flow of crude oil and then petroleum products through this distribution network .
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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