Introduction to Operations ResearchCD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 731
... strategy 1. Player 1 then will receive a payoff of 1 from player 2 ( that is , politician 1 will gain 1,000 votes from politician 2 ) . In general , the payoff to player 1 when both players play optimally is referred to as the value of ...
... strategy 1. Player 1 then will receive a payoff of 1 from player 2 ( that is , politician 1 will gain 1,000 votes from politician 2 ) . In general , the payoff to player 1 when both players play optimally is referred to as the value of ...
Page 733
... strategy 2 instead . Because player 1 is also rational , he would anticipate this switch and conclude that he can ... STRATEGIES 733 Games with Mixed Strategies.
... strategy 2 instead . Because player 1 is also rational , he would anticipate this switch and conclude that he can ... STRATEGIES 733 Games with Mixed Strategies.
Page 734
... strategy 1 or 2 , but he is discarding strategy 3 en- tirely . Similarly , player 2 is randomly choosing between his last two pure strategies . To play the game , each player could then flip a coin to determine which of his two accept ...
... strategy 1 or 2 , but he is discarding strategy 3 en- tirely . Similarly , player 2 is randomly choosing between his last two pure strategies . To play the game , each player could then flip a coin to determine which of his two accept ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost Courseware CPLEX decision variables dual problem dual simplex method dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal programming graphical identify increase initial BF solution integer iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices shown slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero