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Resource-Constrained Project Scheduling

Exact Methods for the Multi-Mode Case

  • Book
  • © 1994

Overview

Authors:
  1. Arno Sprecher

    1. Institut für Betriebswirtschaftslehre, Christian-Albrechts-Universität zu Kiel, Kiel, Germany

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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 409)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XII
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  2. The Model

    • Arno Sprecher
    Pages 1-9

  3. Special Cases

    • Arno Sprecher
    Pages 10-18

  4. Variants and Extensions

    • Arno Sprecher
    Pages 19-23

  5. Types of Schedules

    • Arno Sprecher
    Pages 24-33

  6. A Branch and Bound Algorithm

    • Arno Sprecher
    Pages 34-69

  7. Generation of Instances by ProGen

    • Arno Sprecher
    Pages 70-90

  8. Computational Results

    • Arno Sprecher
    Pages 91-106

  9. An Artificial Intelligence Approach

    • Arno Sprecher
    Pages 107-116

  10. Applications

    • Arno Sprecher
    Pages 117-120

  11. Conclusions

    • Arno Sprecher
    Pages 121-124

  12. Back Matter

    Pages 125-148
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Keywords

About this book

Within a project human and non-human resources are pulled together in a tempo­ raray organization in order to achieve a predefined goal (d. [20], p. 187). That is, in contrast to manufacturing management, project management is directed to an end. One major function of project management is the scheduling of the project. Project scheduling is the time-based arrangement of the activities comprising the project subject to precedence-, time-and resource-constraints (d. [4], p. 170). In the 1950's the standard methods MPM (Metra Potential Method) and CPM (Cri­ tical Path Method) were developed. Given deterministic durations and precedence­ constraints the minimum project length, time windows for the start times and critical paths can be calculated. At the same time another group of researchers developed the Program Evaluation and Review Technique (PERT) (d. [19], [73] and [90]). In contrast to MPM and CPM, random variables describe the activity durations. Based on the optimistic, most likely and pessimistic estimations of the activity durations an assumed Beta­ distribution is derived in order to calculate the distribution of the project duration, the critical events, the distribution of earliest and latest occurence of an event, the distribution of the slack of the events and the probability of exceeding a date. By the time the estimates of the distributions have been improved (d. e.g. [52] and [56]). Nevertheless, there are some points of critique concerning the estimation of the resulting distributions and probabilities (d. e.g. [48], [49] and [50]).

Authors and Affiliations

  • Institut für Betriebswirtschaftslehre, Christian-Albrechts-Universität zu Kiel, Kiel, Germany

    Arno Sprecher

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