Multi-objective optimization design of steel structure building energy consumption simulation based on genetic algorithm

  • Yuan Ren
  • , Saeed Rubaiee
  • , Anas Ahmed
  • , Asem Majed Othman
  • , Sandeep Kumar Arora*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

In order to solve the problems of data acquisition, quantitative analysis and model solving in the field of construction schedule optimization, a construction schedule optimization system based on genetic algorithm was constructed. On this basis, the construction schedule two-stage multi-objective optimization models of "duration-cost"and "fixed duration-resource equilibrium"are established, which aim at the lowest cost and resource equilibrium. Through the investigation and analysis of the project contract documents, the energy consumption and cost of the normal construction and emergency construction state of the contract plan of the basic project part (from the beginning of precipitation activities to the end of +0) are obtained. This section was optimized for the analysis. The genetic algorithm is used to solve the model, and the optimal duration of each process and the optimal start time of non-critical process are determined. The feasibility and effectiveness of the system and model are verified by practical application in the actual project, which provides support for determining the construction schedule scientifically and reasonably and helps to improve the construction schedule technical application effect and construction schedule management level.

Original languageEnglish
Pages (from-to)20-28
Number of pages9
JournalNonlinear Engineering
Volume11
Issue number1
DOIs
StatePublished - 1 Jan 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Yuan Ren et al., published by De Gruyter.

Keywords

  • building energy consumption
  • genetic algorithm
  • integrated optimization
  • steel structure

ASJC Scopus subject areas

  • General Chemical Engineering
  • Modeling and Simulation
  • General Engineering
  • Computer Networks and Communications

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