Objective-driven and Pareto Front analysis: Optimizing time, cost, and job-site movements | Academic Article individual record

© 2016 Elsevier B.V. All rights reserved. Finding the optimized trade-off relationship between cost and time, two important objectives of construction projects, helps project managers and their teams select 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 define this relationship more accurately. These researchers have used different optimization techniques such as the genetic algorithm (GA), ant colony, and fuzzy logic to further explore the relationship. In the present paper, the authors have used their previously introduced construction schedule generator algorithm to present graphical relationships between pre-defined objectives of schedule optimizations. The process starts with developing construction schedules from the project's Building Information Model (BIM) as part of the input along with resource data. Then the process continues with optimization of all developed construction schedules according to the two mentioned objectives along with the introduced job-site movement objective, which mathematically helps the sequence of installation be more logical and practical. Finally generation of a 3D space for all the created and calculated construction schedules in the form of a 3D solution cloud point. These 3D construction schedules show solution cloud points and three Pareto Fronts for the given project.

author list (cited authors)
Faghihi, V., Reinschmidt, K. F., & Kang, J. H.
publication date
Elsevier BV Publisher
published in
  • Pareto Front
  • Construction Project Scheduling
  • Building Information Model
  • Genetic Algorithm
  • Optimization
citation count