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Productivity and Safety Based Model for Construction Site Layout Optimization

Article

Last updated: 13 Dec 2022

Subjects

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Tags

Construction projects
Site-layout
Safety and Environmental Aspects
Optimization
Genetic Algorithms
Productivity and Safety Based Model for Construction Site Layout Optimization
ICASGE'21
Construction Management (COM)

Abstract

A good site layout is vital to ensure the safety of the working environment, and the effective and efficient operations. Site layout planning has significant impact on productivity, costs, and duration of construction. Although construction site layout planning is a critical process, systematical analysis of this problem is always difficult because of the existence of vast number of trades and interrelated planning constraints. Construction site layout planning involves identifying, sizing, and positioning temporary and permanent facilities within the boundary of the construction site. Site layout planning can be viewed as complex optimization problem. The problem has been solved using two distinctly approaches: optimization techniques and heuristics methods. Mathematical optimization procedures have been developed to produce optimal solutions, but they are only applicable for small-scale problems. Artificial Intelligent techniques have been used practically real-life problems. On the other hand, heuristic methods used to produce good but not optimal solutions for large problems. In this paper, an optimization model called ProSafe has been developed for solving site layout planning problem considering safety and environmental issues and actual distance between facilities to improve productivity. Genetic Algorithms is used as an optimization bed for the developed model. In order to validate the performance of the developed model, a real-life construction project was tested. The obtained results proved that satisfactory solutions were obtained.

Categories

Construction Management (COM)

Keywords

Construction projects, Site-layout, Safety and Environmental Aspects, Optimization, Genetic Algorithms

Authors

First Name

Hayhtam

Last Name

Sanad

Affiliation

Faculty of Engineering, Tanta University, Egypt

Email

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City

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Orcid

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Publish Date

14 Jun 2021

Link

https://icasge21.conferences.ekb.eg/article_1043.html

Order

23

Publication Type

Conference

Publication Title

ICASGE'21

Publication Link

https://icasge21.conferences.ekb.eg/

Details

Type

Article

Locale

en

Created At

13 Dec 2022