An overview of ARAS method: Theory development, application extension, and future challenge

Multi-attribute decision-making (MADM) is one of the most important parts in decision-making theory, and related research is becoming more and more popular over the past few years. Investigating that the information could be qualitative and quantitative, and the different measurement units cause difficulties in some MADM problems, the additive ratio assessment system (ARAS) method was proposed. The method tries to solve MADM problems through a simple way efficiently, and at the same time eliminates the influence of different measurement units. Till now, the method has received extensive attention and has been extended to different information environments and application fields. To know about the development of the method and improve the method efficiently, this paper reviews the studies on the ARAS method from the perspectives of basic information (including the bibliometrics analyses and the outline of ARAS method), the development on theory (including the development on MADM mechanism, different information environments, and combination with different methods), the development on the application and the future challenge. From the overview, the basic situations and the development of the ARAS method are presented clearly, and the analyses of the challenges can also provide useful and sufficient instructions for the future application and improvement of the method.

Automated summary

The ARAS method is proposed to efficiently solve MADM problems and eliminate the influence of different measurement units. It has received extensive attention and been extended to different information environments and application fields.