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 115
... slack variable for this constraint is defined to be X3 = 4 - X1 , which is the amount of slack in the left - hand side of the inequality . Thus , = X1 + X3 = 4 . Given this equation , x1 ≤ 4 if and only if 4 x1 = x3 = 0. Therefore ...
... slack variable for this constraint is defined to be X3 = 4 - X1 , which is the amount of slack in the left - hand side of the inequality . Thus , = X1 + X3 = 4 . Given this equation , x1 ≤ 4 if and only if 4 x1 = x3 = 0. Therefore ...
Page 214
... slack variables in rows 1 to 3 of the new tableau , because the coefficients of the slack variables in rows 1 to 3 of the initial tableau form an identity matrix . Thus , just as stated in the verbal description of the fundamental ...
... slack variables in rows 1 to 3 of the new tableau , because the coefficients of the slack variables in rows 1 to 3 of the initial tableau form an identity matrix . Thus , just as stated in the verbal description of the fundamental ...
Page 484
... slack each activity has . The slack for an activity is the difference between its latest finish time and its earliest fin- ish time . In symbols , Slack = LF - EF . ( Since LF EF = LS - ES , either difference actually can be used to ...
... slack each activity has . The slack for an activity is the difference between its latest finish time and its earliest fin- ish time . In symbols , Slack = LF - EF . ( Since LF EF = LS - ES , either difference actually can be used to ...
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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 described dual problem dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau flow following problem formulation functional constraints Gaussian elimination given 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 simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero