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Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008–2018

doi: 10.3390/sym11030350
Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008–2018
Sustainability is one of the main challenges of the recent decades. In this regard, several prior studies have used different techniques and approaches for solving this problem in the field of sustainability engineering. Multiple criteria decision making (MCDM) is an important technique that presents a systematic approach for helping decisionmakers in this field. The main goal of this paper is to review the literature concerning the application of MCDM methods in the field of sustainable engineering. The Web of Science (WoS) Core Collection Database was chosen to identify 108 papers in the period of 2008–2018. The selected papers were classified into five categories, including construction and infrastructure, supply chains, transport and logistics, energy, and other. In addition, the articles were classified based on author, year, application area, study objective and problem, applied methods, number of published papers, and name of the journal. The results of this paper show that sustainable engineering is an area that is quite suitable for the use of MCDM. It can be concluded that most of the methods used in sustainable engineering are based on traditional approaches with a noticeable trend towards applying the theory of uncertainty, such as fuzzy, grey, rough, and neutrosophic theory.
- University of Niš Serbia
- University of Belgrade Serbia
- Universiti Teknologi MARA Malaysia
- University of Defence Serbia
- University of East Sarajevo Bosnia and Herzegovina
HB Economic Theory, engineering, HF Commerce, 001, sustainability, QA1-939, multi-criteria decision-making, Mathematics
HB Economic Theory, engineering, HF Commerce, 001, sustainability, QA1-939, multi-criteria decision-making, Mathematics
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).240 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
