## 6 Conclusions  
The study proposed an integrated framework for multi-criterion temporary facility layout evaluation and decision-making, aiming at optimizing multiple construction objectives and  
\begin{table}
\begin{tabular}{c c c c} \hline
**Rank** & \multicolumn{2}{c}{**Sub-Criterion**} & **Weight Value** & **Criterion.** \\ \hline
1 & Labor productivity and ergonomics (LPE) & 0.1 & Productivity \\
2 & Minimization of the total number of intersections & 0.0976 & Safety \\
3 & Proper equipment operation (PEO) & 0.0878 & Safety \\
4 & Safety of task execution (STE) & 0.0697 & Safety \\
5 & Facility removal cost (FRC) & 0.066 & Cost \\
6 & Control of hazardous zones (CHZ) & 0.0644 & Safety \\
7 & Resource travelling cost (RTC) & 0.0644 & Cost \\
8 & Worksite personnel visit cost (WPC) & 0.0633 & Cost \\
9 & Short construction duration (SCD) & 0.0611 & Productivity \\
10 & Effective space utilization (ESU) & 0.0576 & Productivity \\
11 & Resource handling cost (RHC) & 0.0528 & Cost \\
12 & Workspace conflicts (WSC) & 0.0479 & Productivity \\
13 & Facility setup cost (PSC) & 0.0469 & Cost \\
14 & Control of hazardous material (CHM) & 0.0431 & Safety \\
15 & The ability to dynamically change the TFs (ACT) & 0.0407 & Productivity \\
16 & Facility closeness relationships (FCRs) & 0.0369 & Productivity \\ \hline \end{tabular}
\end{table}
Table 10: Rank of sub-criteria for temporary facility layout planning.  
determining the optimal layout alternative. The proposed framework presented a two-phase decision process, which integrated the ANP approach, simulation-based sensitivity analysis, and optimization methods. The generic temporary facility layout framework and network structure were formulated. With the ANP modeling approach, the spatial layout decision problem was transformed into a multi-criterion mathematical problem. It supports the construction planners and managers in generating the relative importance among objectives and criteria at the practical level and determining the weight value of each criterion in the layout problem. Through the OAT-based simulation, the sensitive factors that significantly impact the layout performance were identified and the potential optimal alternatives were determined.  
In the present research, the proposed model was implemented on an application example to validate its effectiveness and capabilities. From the results of the case study, the overall rankings of sub-criteria were provided to the decision-makers, which indicated that some sub-criteria belonging to the productivity and safety criteria were relatively important. In the application example, it can assist site managers with the decision-making task to determine the optimal solution for temporary facility layout. The most important sub-criteria were identified through the ANP-based model, which were specifically the LPE, minimization of the TNI and PEO. Therefore, the facilities should be arranged reasonably according the evaluation results. Considering the cost impact on layout planning, the facility removal cost should be minimized through effective layout optimization. Furthermore, the sensitivity analysis generated the possible optimal alternatives through the simulation process and help construction planners to avoid selecting the alternatives which would never be the optimal solutions.  
The analysis results highlight the new and unique capabilities of the temporary facility layout planning model in generating the optimal alternative considering multiple criteria. This provides the construction managers and planners with a useful tool to improve the overall performance of temporary facility planning in construction projects.  
[PERSON] drafted the manuscript. [PERSON] and [PERSON] revised the draft and prepared the final manuscript.  
This research was funded by Fundamental Research Funds for the Central Universities (grant number: DUT18 JC44 and 3132018171).  
The authors declare no conflicts of interest.