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Top1. Introduction
Material selection in different engineering disciplines is a fundamental issue and challenging task in the recent years. This arises from the need to deliver products with lower cost and higher efficiency especially in the light of wide range of conflicting criteria that the judge the selection of materials such as environmental impact, performance requirements, aesthetic satisfaction. The selection process is further complicated due to the increase in numbers and types of materials in the last two decades (Chatterjee et al., 2018; Zhang et al., 2017). Additionally, improper selection of materials can result in failure in the performance of products and inability to meet the customers’ requirements. It can also diminish the organization’s productivity which adversely affects its profitability and reputation (Jahan et al., 2012).
In view of the above, there is a strive for an efficient robust decision support system that can enable decision makers to select the most optimum material alternative in the presence of multiple conflicting criteria. Thus, the main objectives of the present research study lie in the following:
- 1.
Develop a hybrid multi-criteria decision making method for selecting the most optimum alternative.
- 2.
Study the degree of correlation between each pair of multi-criteria decision making algorithms.
- 3.
Conduct a sensitivity analysis to investigate the robustness of the utilized multi-criteria decision making algorithms.
Top2. Literature Review
Several multi-criteria decision making models were previously developed for the sake of sustainable assessment of materials in various engineering disciplines. Patnaik et al. (2020) introduced multi-criteria decision making model for composite material selection of structural selection. The materials were selected according to their mechanical, physical and wear properties. Analytical hierarchy process was deployed to find the weighting vector of the attributes. Multi-objective optimization on the basis of ratio analysis algorithm was applied to compare and rank the material alternatives. Ma et al. (2018) proposed multi-criteria decision making model for material selection meanwhile considering life cycle analysis. Gabi software was employed to obtain the environmental equivalents of life cycle. Information entropy method was utilized to compute the weights of attributes. Eventually, technique for order preference by similarity to an ideal solution algorithm was used to prioritize the materials and determine the most optimal one.
Mahmoudkelaye et al. (2018) presented analytical network process-based approach for sustainable material selection of building enclosure. The studied criteria encompassed economic indicators, technical indicators, environmental indicators and socio-cultural indicators. Three alternatives of materials were considered, namely aluminium siding, cedar siding and mortar wall. It was found that aluminium siding is the most sustainable material while cedar siding is the least sustainable material. Marzouk and Mohammed Abdelkader (2020) introduced a hybrid fuzzy optimization-based model for identifying the most sustainable construction alternatives. Multi-objective non-dominated sorting genetic algorithm II was employed to compare the construction alternatives according to the project duration, project lifecycle cost, project overall environmental impact and project total energy consumed. Fuzzy set theory was used to handle the uncertainties encountered during the quantification of the different attributes. TOPSIS algorithm was utilized to determine the most optimum material for each construction component among the Pareto optimal solutions.