Introduction to Operations Research, Volume 1CD-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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Results 1-3 of 77
Page 760
0.25 ( 0.6 ) = 0.15 Oil and FSS 0.15 0.5 0.3 Oil , given FSS 0.6 FSS , given Oil 0.4 USS , given Oil = 0.14 0.1 0.7 Oil , given USS 0.25 0.25 ( 0.4 ) = 0.1 Oil and USS 1 Oil 0.75 0.15 = 0.5 0.3 Dry , given FSS 0.75 ( 0.2 ) = 0.15 Dry ...
0.25 ( 0.6 ) = 0.15 Oil and FSS 0.15 0.5 0.3 Oil , given FSS 0.6 FSS , given Oil 0.4 USS , given Oil = 0.14 0.1 0.7 Oil , given USS 0.25 0.25 ( 0.4 ) = 0.1 Oil and USS 1 Oil 0.75 0.15 = 0.5 0.3 Dry , given FSS 0.75 ( 0.2 ) = 0.15 Dry ...
Page 999
Consider a one - period model where the only two costs are the holding cost , given by Holding cost = $ 0.25 per item , Shortage cost = $ 2 per item , Purchase price $ 1 per item . Stock left over at the end of the final period is ...
Consider a one - period model where the only two costs are the holding cost , given by Holding cost = $ 0.25 per item , Shortage cost = $ 2 per item , Purchase price $ 1 per item . Stock left over at the end of the final period is ...
Page 1187
... win and win 0.818 win , given win 0.75 win , given win lose , given win 0.25 0.6 0.15 win and lose 0.333 win , given lose Win Lose 0.1 0.4 0.182 lose , given win lose and win 0.25 win , given lose lose , given lose 0.75 0.3 0.667 ...
... win and win 0.818 win , given win 0.75 win , given win lose , given win 0.25 0.6 0.15 win and lose 0.333 win , given lose Win Lose 0.1 0.4 0.182 lose , given win lose and win 0.25 win , given lose lose , given lose 0.75 0.3 0.667 ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
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 direction 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