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. |
From inside the book
Results 1-3 of 82
Page xxiv
3.6 describes and illustrates how to use Excel and its Solver to formulate and solve linear programming models on a spreadsheet . ... These files also illustrate how MPL and CPLEX can be integrated with spreadsheets .
3.6 describes and illustrates how to use Excel and its Solver to formulate and solve linear programming models on a spreadsheet . ... These files also illustrate how MPL and CPLEX can be integrated with spreadsheets .
Page 87
The last use above illustrates that this function can be placed on the left of an assignment statement to place solution results into the spreadsheet ... Let us illustrate the ODBC connection for our little product - mix example .
The last use above illustrates that this function can be placed on the left of an assignment statement to place solution results into the spreadsheet ... Let us illustrate the ODBC connection for our little product - mix example .
Page 684
To illustrate this notation , consider the following example of a quadratic programming problem . Maximize f ( x1 , x2 ) = 15x1 + 30x2 + 4x1x2 – 2xí – 4xž , subject to = x1 + 2x2 = 30 and x = 0 , x2 > 0 .
To illustrate this notation , consider the following example of a quadratic programming problem . Maximize f ( x1 , x2 ) = 15x1 + 30x2 + 4x1x2 – 2xí – 4xž , subject to = x1 + 2x2 = 30 and x = 0 , x2 > 0 .
What people are saying - Write a review
We haven't found any reviews in the usual places.
Other editions - View all
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