Alothaimeen, I (2018) Multi-objective optimization for LEED: New construction using genetic algorithms. PhD thesis, Illinois Institute of Technology, USA.
Abstract
In the U.S. , the building sector is responsible for 73% of electricity usage, 38% of CO2 emissions, and 13. 6% of potable water. These data indicate that the construction industry negatively impacts the global environment and natural resources. The concept of “sustainability” was introduced to set guidelines for the construction industry to limit its negative environmental impact. To promote sustainability in the construction industry, many organizations have introduced guidelines and rating systems for buildings. One of these rating systems is Leadership in Energy and Environmental Design (LEED) which is the most globally acknowledged system. Although LEED excels in reducing the negative environmental impacts and the energy consumption of buildings, the high costs in the early phases associated with the implementation and pursuit of LEED certification are pushing away some project owners from entering the process. Therefore, to balance these objectives in sustainable projects, an approach which optimizes multiple objectives is needed. In this study, a multi-objective optimization framework, which uses Non-dominated Sorting Genetic Algorithm-II (NSGA-II), is proposed to find the optimal solution in terms of life-cycle cost and sustainability for a new construction project pursuing LEED v4 BD+C certification. A BIM project of a 3-floor educational building was selected as a case study in the research. The study case is used to verify the efficiency and soundness of the proposed model. The results show that the method does indeed lead to optimal solutions.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Arditi, D |
| Uncontrolled Keywords: | education; efficiency; energy consumption; optimization; sustainability; construction project; natural resources; certification; environmental design; environmental impact; leadership; owner; case study |
| Index terms: | certification, genetic algorithm, educational building, construction project, environmental impact, owner, environmental design, natural resource, efficiency, CO2 emissions, case study, implementation, construction industry, multi-objective optimization, energy consumption |
| Subjects: | performance management, sociology, industry analysis, administrative processes, air quality, data collection methods, sustainability and energy, energy systems, algorithms, production management, construction type, environmental impact, environmental resource management, contractual arrangements |
| Topics: | Research Practice, Construction Technology, Stakeholder Management, Design Practice, Digital Applications, Contract Administration, Project Management, Procurement, Sustainability, Quality Management |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here