An optimization algorithm for simulation-based planning of low-income housing projects
Construction of low-income housing projects is a replicated process and is associated with uncertainties that arise from the unavailability of resources. Government agencies and/or contractors have to select a construction system that meets low-income housing projects constraints including project c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2010-10-01
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| Series: | Journal of Advanced Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090123210000676 |
| _version_ | 1829141421695696896 |
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| author | Mohamed M. Marzouk Osama A. Omar Manal S. Abdel Hamid Moheeb E. El-Said |
| author_facet | Mohamed M. Marzouk Osama A. Omar Manal S. Abdel Hamid Moheeb E. El-Said |
| author_sort | Mohamed M. Marzouk |
| collection | DOAJ |
| description | Construction of low-income housing projects is a replicated process and is associated with uncertainties that arise from the unavailability of resources. Government agencies and/or contractors have to select a construction system that meets low-income housing projects constraints including project conditions, technical, financial and time constraints. This research presents a framework, using computer simulation, which aids government authorities and contractors in the planning of low-income housing projects. The proposed framework estimates the time and cost required for the construction of low-income housing using pre-cast hollow core with hollow blocks bearing walls. Five main components constitute the proposed framework: a network builder module, a construction alternative selection module, a simulation module, an optimization module and a reporting module. An optimization module utilizing a genetic algorithm enables the defining of different options and ranges of parameters associated with low-income housing projects that influence the duration and total cost of the pre-cast hollow core with hollow blocks bearing walls method. A computer prototype, named LIHouse_Sim, was developed in MS Visual Basic 6.0 as proof of concept for the proposed framework. A numerical example is presented to demonstrate the use of the developed framework and to illustrate its essential features. |
| first_indexed | 2024-12-14T20:13:31Z |
| format | Article |
| id | doaj.art-b397cf3e65cb49ee826973d1d74ef76d |
| institution | Directory Open Access Journal |
| issn | 2090-1232 2090-1224 |
| language | English |
| last_indexed | 2024-12-14T20:13:31Z |
| publishDate | 2010-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Advanced Research |
| spelling | doaj.art-b397cf3e65cb49ee826973d1d74ef76d2022-12-21T22:48:54ZengElsevierJournal of Advanced Research2090-12322090-12242010-10-011429130010.1016/j.jare.2010.06.002An optimization algorithm for simulation-based planning of low-income housing projectsMohamed M. Marzouk0Osama A. Omar1Manal S. Abdel Hamid2Moheeb E. El-Said3Structural Engineering Department, Faculty of Engineering, Cairo University, EgyptStructural Engineering Department, Faculty of Engineering, Cairo University, EgyptConstruction and Project Management Research Institute, Housing and Building National Research Center (HBRC), EgyptConstruction Engineering and Management, Structural Engineering Department, Faculty of Engineering, Cairo University, EgyptConstruction of low-income housing projects is a replicated process and is associated with uncertainties that arise from the unavailability of resources. Government agencies and/or contractors have to select a construction system that meets low-income housing projects constraints including project conditions, technical, financial and time constraints. This research presents a framework, using computer simulation, which aids government authorities and contractors in the planning of low-income housing projects. The proposed framework estimates the time and cost required for the construction of low-income housing using pre-cast hollow core with hollow blocks bearing walls. Five main components constitute the proposed framework: a network builder module, a construction alternative selection module, a simulation module, an optimization module and a reporting module. An optimization module utilizing a genetic algorithm enables the defining of different options and ranges of parameters associated with low-income housing projects that influence the duration and total cost of the pre-cast hollow core with hollow blocks bearing walls method. A computer prototype, named LIHouse_Sim, was developed in MS Visual Basic 6.0 as proof of concept for the proposed framework. A numerical example is presented to demonstrate the use of the developed framework and to illustrate its essential features.http://www.sciencedirect.com/science/article/pii/S2090123210000676Construction managementPlanning and schedulingLow-income housingComputer simulationOptimizationGenetic algorithms |
| spellingShingle | Mohamed M. Marzouk Osama A. Omar Manal S. Abdel Hamid Moheeb E. El-Said An optimization algorithm for simulation-based planning of low-income housing projects Journal of Advanced Research Construction management Planning and scheduling Low-income housing Computer simulation Optimization Genetic algorithms |
| title | An optimization algorithm for simulation-based planning of low-income housing projects |
| title_full | An optimization algorithm for simulation-based planning of low-income housing projects |
| title_fullStr | An optimization algorithm for simulation-based planning of low-income housing projects |
| title_full_unstemmed | An optimization algorithm for simulation-based planning of low-income housing projects |
| title_short | An optimization algorithm for simulation-based planning of low-income housing projects |
| title_sort | optimization algorithm for simulation based planning of low income housing projects |
| topic | Construction management Planning and scheduling Low-income housing Computer simulation Optimization Genetic algorithms |
| url | http://www.sciencedirect.com/science/article/pii/S2090123210000676 |
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