## 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 179

x2 2 0. 4.6-8. Consider the following problem. Maximize Z = 2x, + 5x2 + 3x3,

subject to I|_2X2+X322O 2X|+4X2+X3:50 and X120, X220, X320. (a) Using the

Big M ...

**Minimize**Z = 5,000x, + 7,O0Ox2, subject to -2.“ + X2 2 1 X] _ 2X2 Z 1 and x, 2 O,x2 2 0. 4.6-8. Consider the following problem. Maximize Z = 2x, + 5x2 + 3x3,

subject to I|_2X2+X322O 2X|+4X2+X3:50 and X120, X220, X320. (a) Using the

Big M ...

Page 415

9.4 Other Applications Not all applications of the shortest-path problem involve

9.4 Other Applications Not all applications of the shortest-path problem involve

**minimizing**the distance traveled from the origin to the destination. In fact, they ...**Minimize**the total distance traveled, as in the Seervada Park example. 2.**Minimize**...Page 713

Consider the following nonlinear programming problem:

subject to xl + x; = I0 and x, 2 0, x; 2 0. (a) Of the special types of nonlinear

programming problems described in Sec. 13.3, to which type or types can this

particular ...

Consider the following nonlinear programming problem:

**Minimize**z = 2»? + xi,subject to xl + x; = I0 and x, 2 0, x; 2 0. (a) Of the special types of nonlinear

programming problems described in Sec. 13.3, to which type or types can this

particular ...

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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