## 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 249

constructing the dual problem except that the nonnegativity

corresponding dual variable should be deleted (i.e., this variable is ... Another

shortcut involves functional

constructing the dual problem except that the nonnegativity

**constraint**for thecorresponding dual variable should be deleted (i.e., this variable is ... Another

shortcut involves functional

**constraints**in 2 form for a maximization problem.Page 586

Either-Or

between two

other one can hold but is not required to do so). For example, there may be a

choice ...

Either-Or

**Constraints**Consider the important case where a choice can be madebetween two

**constraints**, so that only one (either one) must hold (whereas theother one can hold but is not required to do so). For example, there may be a

choice ...

Page 587

Since y + 1 — y = 1 (one yes) automatically, there is no need to add another

Consider the case where the overall model includes a set of N possible

Since y + 1 — y = 1 (one yes) automatically, there is no need to add another

**constraint**to force these two decisions to be ... K out of N**Constraints**Must HoldConsider the case where the overall model includes a set of N possible

**constraints**...### 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