Congested construction sites, such as urban building projects, often have insufficient exterior space to accommodate all needed temporary facilities and material storage areas. Accordingly, interior building spaces need to be used for material storage while exterior space is left for temporary site facilities. Existing models of site layout and material logistics, however, do not support the utilization of interior spaces due to the complexity of interior space modeling. This paper presents the development of a new congested construction logistics planning (C2LP) model that is capable of modeling and utilizing interior spaces of buildings under construction to generate optimal logistics plans. The proposed C2LP model includes novel computational algorithms to model interior space allocation, complex space constraints, and impact of interior space utilization on activity scheduling. C2LP considers four types of decision variables, material procurement, material storage, facility layout, and scheduling of noncritical activities. The model is implemented by using multi-objective genetic algorithms to generate optimal logistics plans that provide optimal tradeoffs between minimizing total logistics costs and minimizing schedule criticality. The model is evaluated by using an application example to illustrate its capabilities in utilizing interior building space in the logistics plan of congested construction projects.
- Congested sites
- Material logistics
- Site layout planning
ASJC Scopus subject areas
- Control and Systems Engineering
- Civil and Structural Engineering
- Building and Construction