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 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 estimated duration
...
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 estimated duration
...
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 begin by their latest start times . For example , consider activity M in
...
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 begin by their latest start times . For example , consider activity M in
...
Page 498
To help the linear programming model assign the appropriate value to YFINISH ,
given the values of xa , XB , Xy , it is convenient to introduce into the model the
following additional variables . y ; = start time of activity j ( for j = B , C , ... , N ) ...
To help the linear programming model assign the appropriate value to YFINISH ,
given the values of xa , XB , Xy , it is convenient to introduce into the model the
following additional variables . y ; = start time of activity j ( for j = B , C , ... , N ) ...
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activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraint Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible region feasible solutions 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 revised shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero