# A Treatise on Reconnoitering the Suitability of Fuzzy MARCOS for Assessment of Conceptual Designs
## 1 Introduction
The introduction of the fuzzy and rough number theories is to cater to the multifarious units and dimensions of the design features and ensure that the decision process is unprejudiced and there is no allocation of a crisp value to weights of the design features of different units and dimensions or performance of the design concepts in the decision matrix [12]. Depending on the nature and objectives of the decision process and the complexity of the design features, the Triangular Fuzzy Number (TFN) and Trapezoidal Fuzzy Number (TrFN) have been applied as membership functions in different MADM models in order to proffer solutions in the decision process of selecting an optimal conceptual design [1]. Further, since the introduction of the Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) in the year 2020 [13], it has gained attention by researchers and its application has been extended to several fields of applications for decision making. Examples of the areas of application include supplier selection [14; 15; 16; 17; 18], logistics [19; 20], infrastructure and technology assessment [21; 22; 23; 24; 25; 26; 27; 28; 29; 30] and management decisions [31]. At inception, it was applied to assess sustainable supplier selection in the medical industry, which is a very important task in the medical firm that must be strategically addressed because of the quality expected from medical supplies. Considering eight suppliers and twenty-one decision criteria, the MARCOS method was able to define the relationship between the suppliers and the reference values in order to obtain the utility functions of the suppliers and rank them in relation to the reference values [13]. Further, the MARCOS method was applied to determine the response of insurance companies in terms of healthcare services to the COVID-19 pandemic considering its ability to consider a large set of alternatives, decision criteria and sub-criteria without compromising on the stability and computational integrity of the decision process [31]. In order to avoid a vague decision process, the intuitionistic fuzzy membership function was introduced to evaluate ten insurance companies considering five expert opinions and seven decision criteria. The decision process was able to identify payback period, premium price and network as the substantial criteria for evaluating healthcare insurance companies. Also, considering the importance of effective supply chain management to the growth of industries and business and the fact that a sustainable supply chain is essential in running the day-to-day activities of the company, several articles have provided explicit information on the application of the MARCOS method in supplier selection and its integration with other multi-attribute models. An example of this application is the integration of extended VIKOR and MARCOS for sustainable supplier selection in organ transplantation networks for healthcare devices using an interval-valued intuitionistic fuzzy model [32]. [PERSON] and [PERSON] [14] integrated the fuzzy MARCOS model with fuzzy SWARA (Stepwise Weight Assessment Ratio Analysis) in green supply chain management in order to identify the best supplier from alternative suppliers in a textile industry where green and environmentally friendly textile dyes are needed to be supplied in the industries. The implementation of this integrated fuzzy MARCOS with fuzzy SWARA for green supplier selection has also been verified by [PERSON] et al. [33]. The integration of SWARA and MARCOS also finds application in decision making in the logistics field, where a decision was made on inventory classification. The decision process involved the evaluation of fifty products to be stored considering the quantity of the products purchased, their unit price and annual value of purchase [34]. Another important area of application of the MARCOS model is the field of manufacturing.