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 477
Scheduling Individual Activities The PERT / CPM scheduling procedure begins by addressing Question 4 : When can the ... Having no delays means that ( 1 ) the actual duration of each activity turns out to be the same as its esti- mated ...
Scheduling Individual Activities The PERT / CPM scheduling procedure begins by addressing Question 4 : When can the ... Having no delays means that ( 1 ) the actual duration of each activity turns out to be the same as its esti- mated ...
Page 481
Since an activity's immediate successors cannot start until the activity finishes , this rule is saying that the activity must finish in time to enable all its immediate successors to be- gin by their latest start times .
Since an activity's immediate successors cannot start until the activity finishes , this rule is saying that the activity must finish in time to enable all its immediate successors to be- gin by their latest start times .
Page 498
Y ; = start time of activity j ( for j = B , C , ... , N ) , given the values of x ^ , XB , . . XN ( No such variable is needed for activity A , since an activity that begins the project is automatically assigned a value of 0. ) ...
Y ; = start time of activity j ( for j = B , C , ... , N ) , given the values of x ^ , XB , . . XN ( No such variable is needed for activity A , since an activity that begins the project is automatically assigned a value of 0. ) ...
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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 allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero