Efforts are continuously being made by researchers to improve fuel efficiency and to reduce CO2 emissions from the passenger cars. To achieve these goal, recent trend is to make the cars components light in weight for which manufacturing car roofs using natural fiber reinforced composites (NFCs) is one of the method. Several natural fibers (NFs)are available as alternative reinforcements for the fabrication of NFCs. Different NFs possess different properties and therefore, it is necessary to select the most appropriate natural fiber for fabrication of the composites which in turn will lead to the desired performance of the vehicle. Selection of the optimal natural fiber, amongst the several alternatives, is basically a multi criteria decision making (MCDM) problem as selection is based on the evaluation of several conflicting criteria. In this study, twelve alternative natural fibers (Flax,
The best-worst method (BWM) is a multi-criteria decision-making method which works based on a pairwise comparison system. Using such a systematic pairwise comparison enhances consistency and reliability of results. The BWM results in single solution when there are two or three criteria, and for problems with fully-consistent systems, with any number of criteria. To obtain the weights of criteria for not fully-consistent comparison systems with more than three criteria, there may be a multiple optimal solution. Although multiple optimality may be desirable in some cases, in other cases, decision-makers prefer to have a unique optimal solution. This study proposes new models which result in a unique solution. The proposed models have less constraints in comparison with the previous models.
In recent years, multi-criteria sorting problems have become an interesting topic for researchers working on multi-criteria decision-making. ELimination and Choice Expressing REality (ELECTRE)-TRI and FlowSort are well-known approaches suggested for such a classification. The current study aimed to implement ELECTRE-TRI and FlowSort methods in the stock portfolio selection (SPS) as one of the most popular and important decision-making subjects and compare the outcomes of each method to understand how these methods perform in SPS problems. In this study, the best–worst method was applied to determine the weights of criteria. Four approaches for ELECTRE-TRI and 15 approaches for FlowSort were considered. Finally, 19 different approaches were considered to select stocks from a large pool of stocks. Results indicated that the model parameter should be properly defined to minimize inconsistencies and improve the power of the model.
In recent years, multi-criteria decision making (MCDM) is a significant part of operations research (OR) and has become an interesting topic to researcher who works in the data mining (DM) field. The aim of this chapter is to provide an in-depth presentation of the contribution of MCDM in the field of DM. In order to develop a reliable knowledge base on accumulating knowledge from previous studies, we present a review of the usage of MCDM methods in DM field. The chapter presents methodology and application. The result shows that the most usage of MCDM in DM consists of evaluating classification algorithms, weighting criteria, and ranking association rules and clusters. Finally, some future research directions are suggested at the end of chapter.
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