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 734
Although no completely satisfactory measure of performance is available for
evaluating mixed strategies , a very useful one is the expected payoff . By
applying the probability theory definition of expected value , this quantity is n
Expected ...
Although no completely satisfactory measure of performance is available for
evaluating mixed strategies , a very useful one is the expected payoff . By
applying the probability theory definition of expected value , this quantity is n
Expected ...
Page 762
TABLE 15.3 The optimal policy with experimentation , under Bayes ' decision rule
, for the Goferbroke Co. problem Finding from Expected Payoff Expected Payoff
Including Seismic Survey Optimal Action Excluding Cost of Survey Cost of ...
TABLE 15.3 The optimal policy with experimentation , under Bayes ' decision rule
, for the Goferbroke Co. problem Finding from Expected Payoff Expected Payoff
Including Seismic Survey Optimal Action Excluding Cost of Survey Cost of ...
Page 763
C D E F G CA B 1 Expected Payoff with Perfect Information for Goferbroke 2
Alternative Drill Sell Oil 700 90 State of Nature Dry -100 90 * o o o o 8 9 10 11 12
Prior Probability Maximum Payoff 0.25 700 0.75 90 13 Expected Payoff with
Perfect ...
C D E F G CA B 1 Expected Payoff with Perfect Information for Goferbroke 2
Alternative Drill Sell Oil 700 90 State of Nature Dry -100 90 * o o o o 8 9 10 11 12
Prior Probability Maximum Payoff 0.25 700 0.75 90 13 Expected Payoff with
Perfect ...
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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