## Activity Networks: Project Planning and Control by Network Models |

### From inside the book

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Page 81

Of course, if it is possible to lengthen more than one activity, the

choose the most expensive to lengthen, thus ensuring the largest savings. In

naming the various sections of the

giving ...

Of course, if it is possible to lengthen more than one activity, the

**procedure**wouldchoose the most expensive to lengthen, thus ensuring the largest savings. In

naming the various sections of the

**procedure**we have meticulously avoidedgiving ...

Page 156

And in any event, there is a good reason for not making such comparative

analysis even if computing data were available,* namely, that heuristic

Consequently, it is ...

And in any event, there is a good reason for not making such comparative

analysis even if computing data were available,* namely, that heuristic

**procedures**are usually "tailor made" to fit a particular set of conditions.Consequently, it is ...

Page 203

Heuristics enter the tree search in all three basic phases of the approach: (a) in

the definition of the partitioning

and (c) in the philosophy of searching the tree. Here we wish to draw the reader's

...

Heuristics enter the tree search in all three basic phases of the approach: (a) in

the definition of the partitioning

**procedure**, (b) in the calculation of the bounds,and (c) in the philosophy of searching the tree. Here we wish to draw the reader's

...

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### Contents

Structure and Terminology 1 | 18 |

3 COST CONSIDERATIONS | 31 |

DIGRAPHS AND LINE DIGRAPHS | 39 |

Copyright | |

6 other sections not shown

### Other editions - View all

### Common terms and phrases

activity durations activity networks adjacency matrix algorithm allocation analysis analytical application approach approximation arc durations assume assumption Beta beta distribution Chapter completion computing Consider constraints construction cost function critical path critical path method defined denote determine discussion distribution dual equal equations evaluate example exclusive-or expected duration expected value feasible Figure flow GERT given hence heuristic labeled Laplace transform line digraph linear lower bound Mason's rule minimize modified Monte Carlo N/A N/A network of Fig Normally distributed obtained optimal optimum parameters PERT estimate PERT model possible precedence primal probability problem procedure project duration project network random random variables reader realization of node reduce representation result sample schedule Section Semi-Markov Processes SF lag shown in Fig slack solution specified subnetwork subset Table tasks terminal node Theorem tion transmittance variables variance vector yields z-transform