## 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 156

3.3, we pointed out that the values used for the model

c identified in Table 3.3) generally are just ... If it is discovered that the true value

of a sensitive

3.3, we pointed out that the values used for the model

**parameters**(the air, b, andc identified in Table 3.3) generally are just ... If it is discovered that the true value

of a sensitive

**parameter**differs from its estimated value in the model, this ...Page 255

existent, so that the

more than quick rules of thumb provided by ... very helpful to determine the range

of values of the

.

existent, so that the

**parameters**in the original formulation may represent littlemore than quick rules of thumb provided by ... very helpful to determine the range

of values of the

**parameter**over which the optimal solution will remain unchanged.

Page 299

For each of these following

whether this uncertainty might affect either the feasibility or the optimality of the

above basic solution. Specifically, for each

For each of these following

**parameters**, perform sensitivity analysis to determinewhether this uncertainty might affect either the feasibility or the optimality of the

above basic solution. Specifically, for each

**parameter**, determine the allowable ...### What people are saying - Write a review

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### Common terms and phrases

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