## 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 (

number of times during the later stages of postoptimality analysis as well.

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 largenumber of times during the later stages of postoptimality analysis as well.

Page 160

The procedure is

electronic computer had never been invented, undoubtedly you would have

never heard of linear programming and the simplex method. Even though it is

possible ...

The procedure is

**described**in Sec. 7.2. COMPUTER IMPLEMENTATION If theelectronic computer had never been invented, undoubtedly you would have

never heard of linear programming and the simplex method. Even though it is

possible ...

Page 452

(b) Use the algorithm

Describe how this problem fits the network

months) (7 months) (4 months) minimum spanning tree problem. Priority 4

months 3 ...

(b) Use the algorithm

**described**in Sec. 9.3 to solve this shortestpath ... (a)Describe how this problem fits the network

**description**of the Normal 5 months (4months) (7 months) (4 months) minimum spanning tree problem. Priority 4

months 3 ...

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activity additional algorithm alternative amount analysis apply assignment assumed basic variable begin BF solution calculate called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE final flow formulation given gives hour identify illustrate increase indicates initial inventory iteration linear programming machine Maximize mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path payoff perform plant player possible presented Prob probability problem procedure profit programming problem queueing respectively resulting shown shows side simplex method solution solve step strategy Table tableau tion transportation unit waiting weeks