## 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 571

Use dynamic programming to determine how many of the five crates should be

assigned to each of the three stores to

A college student has 7 days remaining before final examinations begin in her ...

Use dynamic programming to determine how many of the five crates should be

assigned to each of the three stores to

**maximize**the total expected profit. 11.3-2.A college student has 7 days remaining before final examinations begin in her ...

Page 573

The cost (in hundreds of dollars) of installing one, two, or three parallel units in

the respective components is given by the ¢°"'P°"¢"t 4

subject to 0.7 X1 +2X2+3X3S x121, x221, x321, and x,, x2, x3 are integers.

The cost (in hundreds of dollars) of installing one, two, or three parallel units in

the respective components is given by the ¢°"'P°"¢"t 4

**Maximize**Z = xixgxg, 0.5subject to 0.7 X1 +2X2+3X3S x121, x221, x321, and x,, x2, x3 are integers.

Page 574

Mmmu z=A+2é subject to >< -~ + R vow lV !° (There are no nonnegativity

constraints.) Use dynamic programming to solve this problem. 11.3-19. Consider

the following nonlinear programming problem.

x2 5 2.

Mmmu z=A+2é subject to >< -~ + R vow lV !° (There are no nonnegativity

constraints.) Use dynamic programming to solve this problem. 11.3-19. Consider

the following nonlinear programming problem.

**Maximize**Z = xfxz, subject to xj +x2 5 2.

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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