## Introduction to Operations Research, Volume 1-- This classic, field-defining text is the market leader in Operations Research -- and it's now updated and expanded to keep professionals a step ahead -- Features 25 new detailed, hands-on case studies added to the end of problem sections -- plus an expanded look at project planning and control with PERT/CPM -- A new, software-packed CD-ROM contains Excel files for examples in related chapters, numerous Excel templates, plus LINDO and LINGO files, along with MPL/CPLEX Software and MPL/CPLEX files, each showing worked-out examples |

### From inside the book

Results 1-3 of 90

Page 69

Each functional constraint The spreadsheet layout

Each functional constraint The spreadsheet layout

**shown**in Fig . 3.14 includes all these components . The parameters for the functional constraints are in rows 5 , 6 , and 7 , and the coefficients for the objective function are in row 8 ...Page 243

6.1 ( and the direct association between variables

6.1 ( and the direct association between variables

**shown**in Table 6.7 ) , the correspondence between basic solutions in the primal and dual problems is a symmetric one . Furthermore , a pair of complementary basic solutions has the same ...Page 283

In the feasible region

In the feasible region

**shown**in Fig . 6.3 , the geometric interpretation of changing the objective function from Z = 3x + 5x2 to Z ( O ) = ( 3 + O ) x + ( 5 – 20x2 is that we are changing the slope of the original objective function ...### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Other editions - View all

### 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 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