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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Page 573
Consider the following integer nonlinear programming problem . Maximize Z = x1x2x } , Parallel Units Component 1 3 Component 2 Component 3 Component 4 subject to 1 2 3 0.5 0.6 0.8 0.6 0.7 0.8 0.7 0.8 0.9 0.5 0.7 0.9 X1 + 2x2 + 3x3 = 10 ...
Consider the following integer nonlinear programming problem . Maximize Z = x1x2x } , Parallel Units Component 1 3 Component 2 Component 3 Component 4 subject to 1 2 3 0.5 0.6 0.8 0.6 0.7 0.8 0.7 0.8 0.9 0.5 0.7 0.9 X1 + 2x2 + 3x3 = 10 ...
Page 574
Consider the following nonlinear programming problem . Minimize Z = xy + 2x x 20 , X2 20 . Use dynamic programming to solve this problem . subject to x } + xż z 2 . ( There are no nonnegativity constraints . ) Use dynamic programming to ...
Consider the following nonlinear programming problem . Minimize Z = xy + 2x x 20 , X2 20 . Use dynamic programming to solve this problem . subject to x } + xż z 2 . ( There are no nonnegativity constraints . ) Use dynamic programming to ...
Page 709
( a ) Of the special types of nonlinear programming problems described in Sec . 13.3 , to which type or types can this particular problem be fitted ? Justify your answer . ( b ) Now suppose that the problem is changed slightly by ...
( a ) Of the special types of nonlinear programming problems described in Sec . 13.3 , to which type or types can this particular problem be fitted ? Justify your answer . ( b ) Now suppose that the problem is changed slightly by ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
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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 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