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 69
Each functional constraint The spreadsheet layout shown in Fig . 3.14 includes
all these components . The parameters for the functional constraints are in rows 5
, 6 , and 7 , and the coefficients for the objective function are in row 8. The values
...
Each functional constraint The spreadsheet layout shown in Fig . 3.14 includes
all these components . The parameters for the functional constraints are in rows 5
, 6 , and 7 , and the coefficients for the objective function are in row 8. The values
...
Page 243
6.1 ( and the direct association between variables shown in Table 6.7 ) , the
correspondence between basic solutions in the primal and dual problems is a
symmetric one . Furthermore , a pair of complementary basic solutions has the
same ...
6.1 ( and the direct association between variables shown in Table 6.7 ) , the
correspondence between basic solutions in the primal and dual problems is a
symmetric one . Furthermore , a pair of complementary basic solutions has the
same ...
Page 365
However , you will see in this section that some tremendous computational
shortcuts can be taken in this method by exploiting the special structure shown in
Table 8.6 . We shall refer to this streamlined procedure as the transportation
simplex ...
However , you will see in this section that some tremendous computational
shortcuts can be taken in this method by exploiting the special structure shown in
Table 8.6 . We shall refer to this streamlined procedure as the transportation
simplex ...
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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 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