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 227
( a ) Use the fundamental insight presented in Sec . 5.3 to identify the missing
numbers in the current simplex tableau . Show your calculations . ( b ) Indicate
which of these missing numbers would be generated by the revised simplex
method in ...
( a ) Use the fundamental insight presented in Sec . 5.3 to identify the missing
numbers in the current simplex tableau . Show your calculations . ( b ) Indicate
which of these missing numbers would be generated by the revised simplex
method in ...
Page 405
For example , both the transportation problem and the assignment problem
discussed in the preceding chapter fall into this category because of their network
representations presented in Figs . 8.3 and 8.5 . One of the linear programming ...
For example , both the transportation problem and the assignment problem
discussed in the preceding chapter fall into this category because of their network
representations presented in Figs . 8.3 and 8.5 . One of the linear programming ...
Page 640
Consider the following nonlinear BIP problem . Maximize Z = 80xı + 60x2 + 40x3
+ 20x4 - ( 7x ; + 5x2 + 3x3 + 2x4 ) ?, subject to 0,1 ( d ) Use the BIP branch - and -
bound algorithm presented in Sec . 12.6 to solve the problem as formulated in ...
Consider the following nonlinear BIP problem . Maximize Z = 80xı + 60x2 + 40x3
+ 20x4 - ( 7x ; + 5x2 + 3x3 + 2x4 ) ?, subject to 0,1 ( d ) Use the BIP branch - and -
bound algorithm presented in Sec . 12.6 to solve the problem as formulated in ...
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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