New Distributed-TOPSIS Approach for Multi-Criteria Decision-Making Problems in a Big Data Context

Abstract

Nowadays, the online environment is extra information-rich and allows companies to offer and receive more and more options and opportunities in multiple areas. Thus, decision-makers have abundantly available alternatives to choose from the best one or rank from the most to the least preferred. However, in the multicriteria decision-making field, most tools support a limited number of alternatives with as narrow criteria as possible. Decision-makers are forced to apply a screening or filtering method to reduce the size of the problem, which will slow down the process and eliminate some potential alternatives from the rest of the decision-making process. Implementing MCDM methods in high-performance parallel and distributed computing environments becomes crucial to ensure the scalability of multicriteria decision-making solutions in Big Data contexts, where one can consider a vast number of alternatives, each being described on the basis of a number of criteria. In this context, we consider TOPSIS one of the most widely used MCDM methods. We present a parallel implementation of TOPSIS based on the MapReduce paradigm. This solution will reduce the response time of the decision-making process and facilitate the analysis of the robustness and sensitivity of the method in a high-dimension problem at a reasonable response time. Three multicriteria analysis problems were evaluated to show the proposed approach's computational efficiency and performance. All experiments are carried out within GCP's Dataproc, a service allowing the execution of Apache Hadoop and Spark tasks in Google Cloud. The results of the tests obtained are very significant and promising.

The purpose of the company beyond its position in the market: The new agent of social development

“…This distortion of the CSR and the SDGs requires significant, knowledge‐based measures to manage the information correctly. Therefore, it is necessary to manage an encyclopedic knowledge of information, considering the transparency provided by technologies (as observed in the factor related to leadership), but also allowing the correct relationship between companies and their stakeholders (Bhimavarapu et al, 2023; Lamrini et al, 2023). The purpose of a company also depends on fundamental conditions of understanding about its own identity.…”