## 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 19

Then, even as personnel changes, the system can be

intervals to provide a specific numerical solution?' This system usually is

computer-based. In fact, a considerable number of computer programs often

need to be used ...

Then, even as personnel changes, the system can be

**called**on at regularintervals to provide a specific numerical solution?' This system usually is

computer-based. In fact, a considerable number of computer programs often

need to be used ...

Page 33

+ c, X, is

constraints. The first m constraints (those with a function of all the variables ai1.x1

+ aizx2 + · · · + aims, on the left-hand side) are sometimes

+ c, X, is

**called**the objective function. The restrictions normally are referred to asconstraints. The first m constraints (those with a function of all the variables ai1.x1

+ aizx2 + · · · + aims, on the left-hand side) are sometimes

**called**functional ...Page 472

Using Microsoft Project The first step with Microsoft Project (commonly

Project) is to enter the information in the activity list (Table 10.1). Choose the

View menu and then select its option

Using Microsoft Project The first step with Microsoft Project (commonly

**called**MSProject) is to enter the information in the activity list (Table 10.1). Choose the

View menu and then select its option

**called**Table. From the resulting submenu, ...### What people are saying - Write a review

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### Common terms and phrases

activity additional algorithm amount analysis apply approach assignment assumed basic variable begin BF solution calculate called changes column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE ﬁrst flow formulation given gives hour identify illustrate increase indicates initial inventory involves iteration linear programming machine Maximize mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path 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