Feng, C-W (1998) Applications of genetic algorithms for multi-objective resource allocation of construction projects under certainty. PhD thesis, University of Illinois at Urbana-Champaign, USA.
Abstract
All facilities, from residential housing to large civil infrastructures, go through the construction phase. The analysis at the construction phase plays a key role in the quality and costs of a construction project. By optimizing construction processes, a project may potentially save up to 5-15% of total project costs. In general, construction engineers need to develop work plans that provide the optimal strategies for executing a project. These strategies, including construction methods, crew sizes, and operation sequences, directly impact how efficiently a project is executed. Many objectives are desired during execution; however, many are in conflict with one another. For example, using more resources will reduce the project duration but the costs may increase. Many of these objectives must be considered simultaneously to achieve the overall optimization--a multi-objective optimization problem. This research investigates the use of GAs (Genetic Algorithms) as the foundation for multi-objective construction process optimization. Based on GA principles, a set of algorithms is developed specifically for construction process analysis and optimization. This set of algorithms is also integrated with simulation techniques to analyze risks and uncertainties while addressing process optimization. Computerized systems based on these algorithms are able to analyze construction processes efficiently and identify the optimal solutions and the associated probabilities for large-scale construction projects.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Liu, L Y and Burns, S A |
| Uncontrolled Keywords: | construction phase; duration; genetic algorithms; optimization; process analysis; residential; resource allocation; simulation |
| Index terms: | construction phase, engineer, computerized system, construction method, construction process, duration, resource allocation, residential housing, project cost, strategy, process analysis, construction project, multi-objective optimization, genetic algorithm |
| Subjects: | economics, profession, algorithms, production management, building construction, resource management, construction type, project delivery, management, computing systems, project controls |
| Topics: | Project Management, Digital Applications, Roles and Professions, Cost Management, Time Control, Site Management, Business Strategy, Construction Technology |
| Descriptive scope: | 2 PC |
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