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Scheduling Optimization Using an Adapted Genetic Algorithm with Due Regard for Random Project Interruptions

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 12, v. 12
Seite(n): 2051
DOI: 10.3390/buildings12122051
Abstrakt:

Current socio-economic conditions impose certain requirements on construction and renovation projects that need new methods making evaluations of construction work performance schedules more reliable. Towards this end, the authors propose a consolidated methodology of construction work scheduling based on the interval estimation technique. The boundaries of the interval, as well as determining minimum and maximum construction time, are obtained by minimizing and maximizing the term of construction work performance by introducing random interruptions into successions of critical and subcritical works. Such reasons for interruptions as the failure of key construction machines, unavailability of labor resources, and accidental man-induced or natural impacts are considered. Risk calculations are employed to devise an approach to evaluating the reliability of construction schedules, including minor schedules designated for single-facility projects and major schedules developed for projects that encompass the construction of groups of buildings and structures. Projects on construction of monolithic reinforced concrete frames of buildings were used to verify the efficiency of the proposed approaches to work performance scheduling.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10699768
  • Veröffentlicht am:
    10.12.2022
  • Geändert am:
    15.02.2023
 
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