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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Results 1-3 of 75
Page 301
(a) Construct the resulting revised final tableau (as a function of 0), and then
convert this tableau to proper form from Gaussian elimination. Use this tableau to
identify the new optimal solution that applies for either 0 = 0 or sufficiently small ...
(a) Construct the resulting revised final tableau (as a function of 0), and then
convert this tableau to proper form from Gaussian elimination. Use this tableau to
identify the new optimal solution that applies for either 0 = 0 or sufficiently small ...
Page 425
Iteration 4: Assign a flow of 2 to the augmenting path O – B – D – T. The resulting
residual network is Iteration 5: Assign a flow of 1 to the augmenting path O - C – E
– D – T. Iteration 6: Assign a flow of 1 to the augmenting path O - C – E – T. The ...
Iteration 4: Assign a flow of 2 to the augmenting path O – B – D – T. The resulting
residual network is Iteration 5: Assign a flow of 1 to the augmenting path O - C – E
– D – T. Iteration 6: Assign a flow of 1 to the augmenting path O - C – E – T. The ...
Page 439
The resulting adjusted network is shown in Fig. 9.16. We shall soon illustrate the
entire network simplex method with this same example, starting with yAB = 0 (
xAB = 10) as a nonbasic variable and so using Fig. 9.16. A later iteration will
show ...
The resulting adjusted network is shown in Fig. 9.16. We shall soon illustrate the
entire network simplex method with this same example, starting with yAB = 0 (
xAB = 10) as a nonbasic variable and so using Fig. 9.16. A later iteration will
show ...
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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
Bibliographic information
| Title | Introduction to Operations Research, Volume 1 Introduction to Operations Research, Frederick S. Hillier McGraw-Hill series in industrial engineering and management science |
| Authors | Frederick S. Hillier, Gerald J. Lieberman |
| Edition | 7, illustrated |
| Publisher | McGraw-Hill, 2001 |
| Original from | the University of Michigan |
| Digitized | 8 Aug 2011 |
| ISBN | 0072416181, 9780072416183 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |