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-k...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.展开更多
文摘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.
