## 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 |

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Page 153

We nearly always have to solve again several times during the model debugging stage (

We nearly always have to solve again several times during the model debugging stage (

**described**in Secs . 2.3 and 2.4 ) , and we usually have to do so a large number of times during the later stages of postoptimality analysis as well .Page 254

Other Applications Already we have discussed two other key applications of duality theory to sensitivity analysis , namely , shadow prices and the dual simplex method . As

Other Applications Already we have discussed two other key applications of duality theory to sensitivity analysis , namely , shadow prices and the dual simplex method . As

**described**in Secs . 4.7 and 6.2 , the optimal dual solution ( vt ...Page 452

Use the algorithm

Use the algorithm

**described**in Sec . 9.4 to find the minimum spanning tree for each of these networks . 9.4-2 . The Wirehouse Lumber Company will soon begin logging eight groves of trees in the same general area .### What people are saying - Write a review

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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