## 2 Related Work
### Decision Support System
MCDA can provide efficient tools that combine several operations that can manage the considered factors and better tackle the difficulties of a construction project [20]. Furthermore, MCDA would be a powerful tool for decision-makers to set and investigate diverse environmental and social aspects. The various types of MCDA can be used according to a project's needs to obtain the required result. The literature provides a wide range of MCDM methods, from well-established models such as AHP, TOPSIS, VIKOR, ELECTRE, and SAW to newer approaches like the Best-Worst Method (BWM) [28], Stepwise Weight Assessment Ratio Analysis (SWARA) [29], and Combined Compromise Solution (CoCoSo) [12]. Newer MCDM models, such as BWM and SWARA, have gained attention for their enhanced criteria weighting and ranking capabilities. BWM, introduced by [PERSON] [28], is designed to provide more consistent weight calculations by requiring decision-makers to compare the best and worst criteria directly. While BWM reduces the number of pairwise comparisons, it may suffer from limited scalability in large-scale decision problems. Similarly, SWARA, developed by [PERSON] et al. [29], emphasizes decision-maker preferences by introducing a stepwise re-evaluation of criteria weights. However, SWARA's reliance on subjective assessments may introduce inconsistencies when applied to complex, multi-criteria infrastructure projects. These limitations highlight the challenge of adopting newer methods as reliable standards in practical decision-making contexts. On the other hand, established MCDM methods continue to be widely utilized due to their proven reliability, transparency, and applicability in infrastructure decision-making. These methods offer well-defined computational frameworks that enable systematic evaluation of multiple criteria, making them suitable for constructability assessments in engineering projects. [PERSON] and [PERSON] [17] have listed the 60 most widely used MCDA methods with their applications in diverse fields. TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), first introduced by [PERSON] et al. [30], is one of the most used MCDA techniques. The ranking process includes creating two matrices: the decision matrix and the weighting matrix. The TOPSIS method is used to scale the alternatives. TOPSIS establishes two distinct sets of ideal and anti-ideal choices. It then ranks the available options by assessing their proximity to the ideal alternatives while measuring their distance from the anti-ideal alternatives. In this context, the ideal alternative seeks to maximize profitability measures while minimizing cost criteria. Conversely, the anti-ideal option emphasizes cost criteria minimization at the expense of profitability [22]. Simple additive weighting (SAW) [31] is another MCDM method that works based on a prominent technique for addressing multi-attribute decision problems. The fundamental principle behind the SAW method involves determining the weighted performance ratings for each alternative across all attributes. The alternative with the highest score is considered the optimal choice. The PROMETHEE (Preference Ranking Organization Method For Enrichment Evaluation) method is a valuable and popular method among others in MCDA, first inventedand developed by [PERSON] et al. [32] in 1986. The implementation of PROMETHEE requires certain prerequisite data, namely the weights and decision-maker priority levels are first and second in a row. PROMETHEE is also a simple method to evaluate conception and application where conflicting criteria with several alternatives will be considered [33]. The COPRAS (Complex Proportional Assessment) method, introduced by [PERSON] et al. [34] in 1994, is supposed to consider a direct and proportionate connection of the perfect solution to the ratio of the anti-ideal solution. COPRAS grades alternatives based on their relative prominence (weight), and the final ranking is built using the positive and negative ideal solutions.