## 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 69

Page 298

C ( a ) Suppose that the

C ( a ) Suppose that the

**estimates**for c , and ca are correct but the**estimates**for both b , and b2 are incorrect . Consider the following four cases where the true values of b , and be differ from their**estimates**by the same percentage ...Page 487

Intuitively , this formula is placing most of the weight on the most likely

Intuitively , this formula is placing most of the weight on the most likely

**estimate**and then small equal weights on the other two**estimates**. MS Project provides the option of calculating u for each activity with this formula .Page 517

Using the PERT three -

Using the PERT three -

**estimate**approach , the three**estimates**for one of the activities are as follows : optimistic**estimate**30 days , most likely**estimate**36 days , pessimistic**estimate**48 days . What are the resulting**estimates**of ...### 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