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A Brief Review on Multi-Attribute Decision Making in the Emerging Fields of Computer Science

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Computational Intelligence in Communications and Business Analytics (CICBA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1579))

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Abstract

The decision-making mechanism plays a critical role in assisting experts to estimate and choose the best potential alternatives in this technical age. Multi-Attribute Decision Making (MADM) approaches are commonly utilized in many environments where there are several criteria that need to be evaluated and it is highly challenging to find the best solution. Many MADM innovations have been implemented over the past couple of decades in many fields of computer science that have enabled decision-makers to reach eminent choices. This paper explored the usage of MADM, which is a sub-domain of Multi-Criteria Decision Making, and its applications in 3 emerging and trending computer science fields viz., Cloud Computing, Internet of Things (IoT) and Big Data.

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Authors and Affiliations

  1. Department of Computer Science, Assam University, Silchar, Assam, India

    Satyabrata Nath & Purnendu Das

  2. Department of Applied Science and Humanities, Assam University, Silchar, Assam, India

    Pradip Debnath

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  1. Satyabrata Nath
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  1. Assam University, Silchar, India

    Somnath Mukhopadhyay

  2. Assam University, Silchar, India

    Sunita Sarkar

  3. Visva-Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

  4. University of Kalyani, Nadia, India

    Jyotsna Kumar Mandal

  5. Assam University, Silchar, India

    Sudipta Roy

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Nath, S., Das, P., Debnath, P. (2022). A Brief Review on Multi-Attribute Decision Making in the Emerging Fields of Computer Science. In: Mukhopadhyay, S., Sarkar, S., Dutta, P., Mandal, J.K., Roy, S. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2022. Communications in Computer and Information Science, vol 1579. Springer, Cham. https://doi.org/10.1007/978-3-031-10766-5_1

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