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 732
The end product of this line of reasoning is that each player should play in such a
way as to minimize his maximum losses whenever the resulting choice of
strategy cannot be exploited by the opponent to then improve his position . This
so ...
The end product of this line of reasoning is that each player should play in such a
way as to minimize his maximum losses whenever the resulting choice of
strategy cannot be exploited by the opponent to then improve his position . This
so ...
Page 734
To illustrate , suppose that players 1 and 2 in variation 3 of the political campaign
problem ( see Table 14.5 ) select the ... This selection would say that player 1 is
giving an equal chance ( probability of 2 ) of choosing either ( pure ) strategy 1 or
...
To illustrate , suppose that players 1 and 2 in variation 3 of the political campaign
problem ( see Table 14.5 ) select the ... This selection would say that player 1 is
giving an equal chance ( probability of 2 ) of choosing either ( pure ) strategy 1 or
...
Page 744
For each of the following payoff tables , determine the opIf both product
improvements are developed simultaneously , timal strategy for each player by
successively eliminating dominated either manufacturer can have them ready for
sale in 12 ...
For each of the following payoff tables , determine the opIf both product
improvements are developed simultaneously , timal strategy for each player by
successively eliminating dominated either manufacturer can have them ready for
sale in 12 ...
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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