Abstract
Over the last century, the complexity of construction projects has increased exponentially and its factors (e.g., time, budget, and quality) have generated complicated trade-offs. This research focuses on the trade-off between time, cost, and sustainability represented in Leadership in Energy and Environmental Design (LEED) credits (particularly materials and resources). The research is broken into preliminary and validation studies wherein the preliminary study uses an exhaustive search to find the optimized solution. In the validation case study, dataset size increased exponentially, and it became computationally incompatible to find the optimized solution. Genetic algorithm (GA) is used to find the optimized solution based on user-defined priority factors. Usage of GA is validated using the preliminary study data and then applied to the validation study data. A trade-off is seen between the priority factors and the optimized solution. The optimization model is successful in minimizing the time and cost, concurrently maximizing the points associated with LEED credits for a validation case study.
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