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

### From inside the book

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Page 203

Naturally, we are always interested in the procedure that yields the greatest lower

bound, because then the bounds

Unfortunately, such power of discrimination is either not known or not achievable

...

Naturally, we are always interested in the procedure that yields the greatest lower

bound, because then the bounds

**obtained**are uniformly the most powerful.Unfortunately, such power of discrimination is either not known or not achievable

...

Page 244

As is almost always the case, the improved result is

of extra computing effort. However, as we see below, under the assumption of

independence of arc durations, the total effort is still well below the effort required

...

As is almost always the case, the improved result is

**obtained**at a cost, in the formof extra computing effort. However, as we see below, under the assumption of

independence of arc durations, the total effort is still well below the effort required

...

Page 273

The results are shown in Table 4.5, together with the values

Martin's approach. The results are remarkably good. However, they leave some

doubts on the precision of Martin's results, since the lower bounds for values of y

= 2\ ...

The results are shown in Table 4.5, together with the values

**obtained**usingMartin's approach. The results are remarkably good. However, they leave some

doubts on the precision of Martin's results, since the lower bounds for values of y

= 2\ ...

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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

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### 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