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 130
The model probably has been misformulated , either by omitting relevant
constraints or by stating them incorrectly . Alternatively , a computational mistake
may have occurred . Multiple Optimal Solutions We mentioned in Sec . 3.2 (
under the ...
The model probably has been misformulated , either by omitting relevant
constraints or by stating them incorrectly . Alternatively , a computational mistake
may have occurred . Multiple Optimal Solutions We mentioned in Sec . 3.2 (
under the ...
Page 278
With the current value of C2 = 3 , the optimal solution is ( 4 , 3 ) . When c2 is
increased , this solution remains optimal only for c2 < 4. For c2 2 4 , ( 0 , 3 )
becomes optimal ( with a tie at c2 = 4 ) , because of the constraint boundary 3xı +
4x2 = 18.
With the current value of C2 = 3 , the optimal solution is ( 4 , 3 ) . When c2 is
increased , this solution remains optimal only for c2 < 4. For c2 2 4 , ( 0 , 3 )
becomes optimal ( with a tie at c2 = 4 ) , because of the constraint boundary 3xı +
4x2 = 18.
Page 400
C ( b ) Obtain an optimal solution . ( c ) Reformulate this assignment problem as
an equivalent transportation problem with two sources and three destinations by
constructing the appropriate parameter table . c ( d ) Obtain an optimal solution ...
C ( b ) Obtain an optimal solution . ( c ) Reformulate this assignment problem as
an equivalent transportation problem with two sources and three destinations by
constructing the appropriate parameter table . c ( d ) Obtain an optimal solution ...
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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