Faghihi, V.; Reinschmidt, K.; and Kang, J. (2016) "Objective-driven and Pareto Front Analysis: Optimizing Time, Cost, and Job-site Movements", Automation in Construction, Volume 69, September 2016, Pages 79-88, ISSN 0926-5805, DOI: 10.1016/j.autcon.2016.06.003
Objective-driven and Pareto Front Analysis: Optimizing Time, Cost, and Job-site Movements
Faghihi, V.; Reinschmidt, K.; and Kang, J.
Finding the optimized trade-off relationship between the two main objectives of the construction projects (i.e. cost and time) helps the project managers and their teams in selecting a more suitable schedule for a given project. This trade-off relationship can roughly be estimated using past and cumulative knowledge, but since the early 1970s, researchers have been working on a systematic and mathematical solution to find this relationship more accurately. Those researchers have used different optimization techniques such as the Genetic Algorithm (GA), ant colony, and fuzzy logic for finding the relationship. In the present paper, the authors have used their newly introduced construction optimization objective (i.e. job-site movement) along with cost and time in their GA optimization process. The entire process includes developing construction schedules from the 3D model input of the project along with resource data, optimizing the developed construction schedules toward the three defined objectives, and finally generating a 3D space of all the created and calculated construction schedules. These 3D construction schedules show the solutions cloud points and three Pareto Fronts for the given project.
Keywords: Pareto Front, Optimization, Genetic Algorithm, Construction Project Scheduling