izpis_h1_title_alt

IFC-based schedule optimization : master thesis
ID Njuguna, Melody Wanjiku (Author), ID Cerovšek, Tomo (Mentor) More about this mentor... This link opens in a new window, ID Parente, Manuel (Comentor)

.pdfPDF - Presentation file, Download (4,77 MB)
MD5: FD3A9596D29365A4096C9EAD56D8518D

Abstract
A construction or demolition scheduling problem with resource allocation has both the challenge of sequencing the correct order of works to the elements being constructed or demolished, and assigning the correct labour teams to do this work. Solving this problem requires the knowledge of a wide array of factors, from sequence to coordination of trades, to safety and skill. Even though scheduling and resource allocation problems have been studied at length in the past century, the current existence of modern technologies, i.e. Building Information Modelling and Evolutionary Algorithms, promises the potential to create new ways of solving these problems. This study explores literature on the confluence of these two technologies in the specific context of schedule optimization, and then proposes a method of performing schedule and resource optimization for construction and demolition, based on IFC models and their elements' GUIDs. With the use of a precedence matrix and a chromosome repair strategy, an evolutionary algorithm, NSGA-II is used to generate multiple results bearing optimal schedule orders, and construction and deconstruction costs and times. The methodology is then tested on two case studies, where its efficacy is proven on a demolition problem and a simplified construction problem. The findings of the study show the potential for use of the proposed schedule optimization system within construction and demolition, and proposals are made on methods and strategies to build upon and extend this work.

Language:English
Keywords:master thesis, civil engineering, evolutionary algorithms, genetic algorithms, optimization
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Place of publishing:Ljubljana
Publisher:[M. W. Njuguna]
Year:2024
Number of pages:1 spletni vir (1 datoteka PDF (XVII, 84 str.))
PID:20.500.12556/RUL-162788-047b5678-331f-8906-4578-9b455b9fafd5 This link opens in a new window
UDC:004:421:69(043.2)
COBISS.SI-ID:209687043 This link opens in a new window
Publication date in RUL:27.09.2024
Views:93
Downloads:462
Metadata:XML DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Secondary language

Language:Slovenian
Title:Optimizacija terminskega plana na osnovi IFC : magistrsko delo
Abstract:
Težava pri planiranju gradnje ali rušenja z dodeljevanjem virov predstavlja tako izziv zaporedja pravilnega vrstnega reda del glede na elemente, ki se gradijo ali rušijo, kot tudi dodelitev ustreznih delovnih skupin za opravljanje tega dela. Reševanje tega problema zahteva poznavanje vrste dejavnikov, od zaporedja do koordinacije opravil, do varnosti in potrebnih znanj ter spretnosti. Čeprav so bili problemi razporejanja in dodeljevanja virov obširno preučevani v preteklem stoletju, obstoj sodobnih tehnologij, tj. informacijskih modelov zgradb in evolucijskih algoritmov, daje potencial za izdelavo novih načinov reševanja teh problemov. Ta študija najprej raziskuje literaturo na preseku dveh tehnologij v posebnem kontekstu optimizacije terminskov planov, nato pa predlaga metodo izvajanja optimizacije urnika in virov za gradnjo in rušenje, ki temelji na modelih IFC in GUID (angl. Globally Unique Identifiers) njihovih elementov. Z uporabo prednostne matrike in strategije popravljanja kromosomov se evolucijski algoritem NSGA-II uporablja za generiranje več rezultatov z optimalnimi vrstnimi redi ter stroški in časi gradnje ter dekonstrukcije. Metodologijo nato testiramo na dveh študijah primerov, kjer dokažemo njeno učinkovitost na problemu rušenja in na poenostavljenem problemu gradnje. Ugotovitve študije kažejo potencial za uporabo predlaganega sistema za optimizacijo urnika pri gradnji in rušenju, podani pa so tudi predlogi o metodah in strategijah za nadgradnjo in razširitev tega dela.

Keywords:magistrska dela, gradbeništvo, BIM, evolucijski algoritmi, genetski algoritmi, IFC, optimizacija, NSGA-II

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back