## 1 Introduction  
In construction projects, site layout planning is a critical task for managers and planners to provide labor crews with ergonomic working space and comfortable industrial environment [1]. Within a construction site, temporary facilities, such as equipment (e.g., cranes and scaffoldings), job offices, storage areas, warehouse, fabrication shops, and batch plants, are needed by work crews to support their task operations and various activities [2; 3; 4; 5]. In order to improve the project profitability, labor productivity, safety, quality and controlling ability of project cost, the project managers need to conduct an effective temporary facility layout planning process properly during the construction planning phase [6; 7; 8]. An appropriate layout plan of facilities can reduce the construction expenses by up to 50 percent [9; 10]. Generally, the construction site layout planning problem is to identify the number and size of temporary facilities to be laid out, and the spatial constraints between different facilities. The relative positions and relationships among the facilities are analyzed to construct the project effectively and efficiently [11; 12; 13; 14]. To improve the ability for temporary facility layout planning, a number of research studies were conducted. Different approaches and tools were applied to site layout planning, which mainly include: simulation methods, knowledge-based approaches, genetic algorithms, GISand other optimization methods [5; 14; 15]. For example, [PERSON] and [PERSON] [8] developed an expanded site layout planning model in order to maximize construction safety and minimize the travel cost of multiple resources in construction using multi-objective genetic algorithms. As temporary facility layout planning involves a large number of facilities, the planning process is very labor-intensive and complex. The artificial intelligence-based systems and knowledge-based techniques can also be adopted to deal with the large amounts of layout planning data and further improve the flexibility to the existing temporary facility layout models [16]. In order to improve safety performance and labor productivity, optimum layout of temporary facilities can be generated through simulation-based methods within the restricted sites [2; 17]. The optimization criteria involved in temporary facility planning were identified to assist with the planning task using heuristic algorithms [6; 9; 18; 19; 20; 21; 22; 23]. To automate layout planning, Building Information Modeling (BIM) -based system can support the dynamic generation of site layout models, instead of manually inputting the information data [24]. These attempts have shown the effectiveness and improvements in the temporary facility layout planning and optimization, especially in establishing the mathematical models and identifying the related criteria to solve the complex multi-objective optimization problem. In construction layout planning, the temporary facility layout optimization is a multi-criteria optimization problem, including safety, labor productivity and cost goals. Managers and planners need to identify the factors that affect the performance of a temporary facility layout plan, recognize the space requirements of task executions and select the most economic and productive layout plan from a set of potential alternatives. Each potential alternative may lead to a unique performance on the project. It remains a decision problem to select the optimal or favorable layout plan in the preconstruction phase. To choose the optimal temporary facility layout plan for construction projects, all relevant criteria should be simultaneously considered and further integrated into the decision model. Therefore, a suitable multi-criteria decision-making (MCDM) method is required to assess the performance of different layout plans.