## 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

By applying the probability theory definition of expected value , this quantity is n Expected

By applying the probability theory definition of expected value , this quantity is n Expected

**payoff**for player 1 = PijXiYj i = 1 ... In the example of mixed strategies just given , there are four possible**payoffs**( -2 , 2 , 4 , -3 ) ...Page 752

Therefore , with the

Therefore , with the

**payoff**in units of thousands of dollars of profit , the**payoff**table can be obtained directly from Table 15.1 , as shown in Table 15.2 . We will use this**payoff**table next to find the optimal action according to ...Page 762

TABLE 15.3 The optimal policy with experimentation , under Bayes ' decision rule , for the Goferbroke Co. problem Finding from Expected

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 ...### What people are saying - Write a review

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activity additional algorithm allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible region FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming Maximize million Minimize month needed node nonbasic variables objective function obtained operations optimal optimal solution original parameters path Plant possible presented primal problem Prob procedure profit programming problem provides range remaining resource respective resulting shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit weeks Wyndor Glass zero