# A Typology Model of Temporary Facility Constraints for Automated Construction Site Layout Planning
## 7 Conclusions  
This study contributes to the CSLP automation theories by providing a constraint typology model and suggesting computational modeling of each constraint type, which enables automated constraint checking for improving practicality of construction site layout optimization. The typology model was developed by applying the triangulation approach involving literature review, in-depth interviews with experts, and case studies. As a result, 42 constraint instances utilized in \(11\) temporary facilities were identified and mapped onto the following six constraint types:  
* Dimensional constraints that are related to the size (length, width, area), shape, and direction of the temporary facilities to be laid out; although they can be easily checked through a comparison with the parameters of the temporary facility objects, additional computational modeling is often needed to determine reference values of the constraints themselves. This study identified three constraint instances for this type. * Regional constraints that concern the region in which a temporary facility is allocated; the region includes the site boundaries and a specific enclosed area that exists at the site. This constraint is divided into three subtypes, i.e., boundary (one instances), inclusion area (four instances), and exclusion area (six instances) constraints. They can be modeled through a set of coordinate values occupied by the region and often require site geometry information for accurate evaluation. * Relocation constraints that limit the number of relocations of the facilities during construction; they can be checked by using a binary variable whose value changes when relocation occurs in two consecutive phases. This study identified one constraint instance for this type. * Non-overlap constraints that prevent physical overlap between temporary facilities and other objects; it is also possible to set the offset distance to allow a safety distance between the objects. This constraint type needs to be checked before inter-facility distance constraint checking because they are mandatory requirements for locating temporary facilities on site. * Inter-facility distance constraints that limit the distance between temporary facilities and other objects for several reasons such as safety, security, and accessibility; this constraint is divided into four subtypes, i.e., min distance (12 instances), max(L) distance (two instances), max(T) distance (six instances), and min-max distance (three instances) constraints. The reference points for distance calculation should be set differently depending on the goal of constraints. In addition, travel path distance should be calculated based on estimation of the actual path that are affected by material types and transportation modes. * Visibility constraints that examine the visibility from temporary facilities to other objects or a specific point on the site; this constraint can be checked using ray casting, which projects a light ray from the reference point and displays the visibility region. This study identified three constraint instances for this type. This study is novel because it proposes a CSLP constraint typology model with clarity, substantiality, and comprehensiveness through the collection of the actual constraints required for the layout of major temporary facilities and classification of them according to the computational modeling approach. Findings of this study can be used for the construction site layout optimization process of most construction projects or in the check of compliance with the constraints of the existing BIM-based construction site layout model, thereby contributing to the CSLP automation and improvements in the practical applicability of the results. However, it also poses limitations in that the subjects for the collection of the constraints were limited. Further investigation of constraints from more cases with different characteristics, such as locations, uses, and sizes, would improve the model in terms of generality.