## 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

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Page 166

The two basic factors that determine the performance of an algorithm on a real

problem are the average computer time per

. Our next comparisons concern these factors . Interior - point algorithms are far ...

The two basic factors that determine the performance of an algorithm on a real

problem are the average computer time per

**iteration**and the number of**iterations**. Our next comparisons concern these factors . Interior - point algorithms are far ...

Page 330

Step 5 : 1365 656 3227 656 x = Di 2.08 4.92 1.00 is the trial solution for

3 . Since there is little to be learned by repeating these calculations for additional

Step 5 : 1365 656 3227 656 x = Di 2.08 4.92 1.00 is the trial solution for

**iteration**3 . Since there is little to be learned by repeating these calculations for additional

**iterations**, we shall stop here . However , we do show in Fig . 7.7 the ...Page 371

At each

consideration is calculated and displayed , the largest difference is circled and

the smallest unit cost in its row or column is enclosed in a box . The resulting ...

At each

**iteration**, after the difference for every row and column remaining underconsideration is calculated and displayed , the largest difference is circled and

the smallest unit cost in its row or column is enclosed in a box . The resulting ...

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### 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