## 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 86

Page 69

Finally , the value of the

Finally , the value of the

**objective function**is entered in cell E8 . Much like the other values in column E , it is the sum of products . The equation for cell E8 is = SUMPRODUCT ( C8 : D8 , C9 : D9 ) . The lower right - hand side of ...Page 148

Begin with their

Begin with their

**objective functions**. Big M Method : Minimize Z = 0.4x1 + 0.5x2 + Mã4 + Mło . Two - Phase Method : Phase 1 : Phase 2 : Minimize Minimize Z = X4 + 6 Z = 0.4x1 + 0.5x2 . Because the MX4 and MX terms dominate the 0.4x ...Page 273

Analyzing Simultaneous Changes in

Analyzing Simultaneous Changes in

**Objective Function**Coefficients . Regardless of whether x ; is a basic or nonbasic variable , the allowable range to stay optimal for Cj is valid only if this**objective function**coefficient is the only ...### 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