## 6 Conclusions  
This paper proposed a multi-criteria decision-making model for fall protection planning to assist construction safety management and accident prevention processes from the design phase to the evaluation phase. Since the majority of safety-related research in construction mainly focus on fall prevention techniques and injury analysis, this research focuses on the fall protection plan evaluation and selection to enhance productivity and cost goals during safety management in construction projects. In this paper, a fall protection MCDM system was developed with four identified main criteria and fourteen sub-criteria, and a fuzzy decision-making model was proposed for the plan evaluation and selection process. The model, main theories and the methodology are described in detail. The application process of the proposed model integrates various multi-criteria decision-making approaches, including AHP, fuzzy sets, TOPSIS and simulation-based sensitivity analysis, and develops a framework to select the optimal fall protection plan for construction projects, which is novel and effective for safety optimization in construction projects. The proposed model combines AHP, fuzzy sets and TOPSIS techniques to find the optimal fall protection system plan in construction projects. The priority weights of criteria in the safety evaluation system are effectively generated from AHP. Since there is a high level of uncertainty and ambiguity involved in the fall protection decision-making process, a fuzzy TOPSIS-based model was conjointly adopted for performance evaluation and alternative selection. This decision-making model utilizes construction planners and experts' opinions to assess fall protection plan alternatives according to performance scores of four main criteria and fourteen sub-criteria. Since the descriptions of human opinions may be complex and inaccurate, fuzzy set theory is employed to integrate quantitative assessment criteria in one single algorithm. Usage of fuzzy TOPSIS reflects the vagueness of the safety expert perceptions during the subjective judgment process. The simulation-based sensitivity analysis validates the stability and robustness of alternative ranking results. The results show that the AHP and fuzzy TOPSIS integrated multi-criteria model can enable a novel and effective procedure for decision-makers to evaluate multiple potential alternatives and select the optimal fall protection system plan along with setting productivity and cost goals without compromising the safety objective in construction management. Figure 9: 3D histogram plot for performance changes in C5 main changing conditions. Considering the limited number of sub-criteria in the assessment hierarchy, it is necessary to add more assessment criteria to improve the result accuracy of the multi-criteria decision-making method in future research. Moreover, to implement the decision-making approach into industry practices, the method can be further integrated into an automated BIM-based safety planning system. The proposed multi-criteria decision-making framework can be embedded into an automated system, where the preference information can be incorporated into the system to automatically generate the optimal safety plan. Therefore, based on the presented framework, construction managers can utilize the decision-making tool to select the optimal safety plan for various hazardous work areas on jobsites. Conceptualization, H.J. and P.M.G. ; methodology, H.J. ; software H.J. ; validation, H.J. and P.M.G. ; writing--original draft preparation, H.J. ; writing--review and editing, H.J. and P.M.G. ; supervision, P.M.G. All authors have read and agreed to the published version of the manuscript. This research was supported by the China Postdoctoral Science Foundation (grant number 2020M680355) and Fundamental Research Funds for the Chinese Central Universities (grant number FRF-TP-20-020A1). Not applicable. The data presented in this study are available on request from the corresponding author. The authors declare no conflict of interest.