Overview of Multi-Objective Optimization Approaches in Construction Project Management

The difficulties that are met in construction projects include budget issues, contractual time constraints, complying with sustainability rating systems, meeting local building codes, and achieving the desired quality level, to name but a few. Construction researchers have proposed and construction practitioners have used optimization strategies to meet various objectives over the years. They started out by optimizing one objective at a time (e.g., minimizing construction cost) while disregarding others. Because the objectives of construction projects often conflict with each other, single-objective optimization does not offer practical solutions as optimizing one objective would often adversely affect the other objectives that are not being optimized. They then experimented with multi-objective optimization. The many multi-objective optimization approaches that they used have their own advantages and drawbacks when used in some scenarios with different sets of objectives. In this chapter, a review is presented of 16 multi-objective optimization approaches used in 55 research studies performed in the construction industry and that were published in the period 2012–2016. The discussion highlights the strengths and weaknesses of these approaches when used in different scenarios

MULTI-OBJECTIVE OPTIMIZATION FOR LEED - NEW CONSTRUCTION USING GENETIC ALGORITHMS

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