# Integrated Decision Support Framework of Optimal Scaffolding System for Construction Projects
###### Abstract
The authors claimed that qualitative criteria should also be considered in scaffolding planning practices. A comprehensive framework was proposed by [PERSON] et al. [10] for assessing and selecting scaffolding. The framework was based on the analytic hierarchy process that incorporated expert knowledge into the selection process. In this study, the scaffoldings alternatives were limited to two scaffolding types: metal scaffolding and bamboo scaffolding. [PERSON] et al. [15] developed seven decision trees to describe scaffolding space requirements according to in-depth interviews and developed a decision supporting model that could be applied to planning and allocating scaffolding systems based on expert knowledge. [PERSON] et al. [16] developed a decision-making framework to create effective scaffolding plans regarding safety, cost, and duration based on quantitative evaluation and expert judgment. With supported scaffolding, tower scaffolding, suspended scaffolding and mast climber, the framework was able to select the final scaffolding plan based on expert judgements to enhance construction safety and reduce duration and cost. As addressed previously, there are several studies in the literature that assist temporary facility planners when evaluating the performance of different scaffolding systems for the jobsite. However, decisions regarding scaffolding planning are limited to several influential factors, and the decision-making process is currently mainly based on the knowledge and experience of construction planners, rather than a systematic and automated path. Therefore, the scaffolding planning process is completed without the assistance of automatic approaches that consider a set of quantitative and qualitative criteria, so the solutions cannot be directly generated. Therefore, there is a need to develop an effective framework and robust model that can be used in actual industry practices. Multi-criteria decision-making (MCDM) methods have been widely used in construction management [17; 18; 19; 20; 21; 22]. [PERSON] [23] provided in-depth discussions on fuzzy hybrid techniques applied in construction, including optimization problems, multicriteria decision making, and simulation. [PERSON] et al. [24] developed a methodology for the selection of mobile cranes based on an integrated approach of the analytical hierarchy process (AHP) and multi-attribute utility theory (MAUT). [PERSON] et al. [25] developed a fuzzy-TOPSISframework for supplier selection, which can compare the competence and readiness of different firms. [PERSON] et al. [26] proposed a TOPSIS-based framework for selection of the construction material supply chain that enhances sustainability. [PERSON] et al. [27] proposed a supplier selection framework based on AHP and grey relational analysis for construction projects. [PERSON] et al. [28] presented an AHP-based supplier selection method for a prefabrication project that prioritized the criteria and supplier alternatives. [PERSON] and [PERSON] [29] developed a decision-making framework to assess sustainability for residential buildings based on AHP and BIM. [PERSON] et al. [30] proposed a three-phase assessment model to select material for construction through the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach. [PERSON] et al. [31] developed a TOPSIS-based framework for the selection of concrete mixture sustainability design. [PERSON] and [PERSON] [32] proposed a framework for the selection of renovation solutions for residential buildings based on TOPSIS and applied the framework effectively in two cases. Based on the existing multi-criteria decision-making techniques for construction projects, this paper proposes a novel framework for a knowledge-based decision-making system of scaffolding selection through fuzzy multi-criteria decision-making analysis. The main contributions to the body of knowledge are as follows: first, this study proposes a knowledge-based scaffolding decision support system that integrates two-phase simulation modules and algorithms.