A review of clustering techniques for waste management

• Published in: Heliyon Vol. 8; no. 1; p. e08784
• Main Authors: Assef, Fernanda Medeiros, Steiner, Maria Teresinha Arns, Lima, Edson Pinheiro de
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.01.2022; Elsevier
• Subjects: Landfill location; Review; Systematic literature review; Waste collection; Waste management; Waste management; Landfill location; Waste collection; Systematic literature review
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2022.e08784

A variety of problems related to waste management systems can be found in the literature, as they have become tougher to solve over the years. With this in mind, a report of the most influential research concerns in this field could help develop innovative works for solving waste management applications. Literature reviews appear in most introductions and discussion sections of research reports, case reports, and expert opinion papers. It was immediately observed that Cluster Analysis, a multivariate data mining technique, has been used in various applications for sustainability issues. For this reason, this paper shows the results of a Systematic Literature Review on Cluster Analysis techniques applied to waste management. This paper's primary goal is to detect what is happening with the applications and techniques in clustering techniques for waste management and, in this way, define possible gaps in this research field. The 61 analyzed papers were categorized into nine application types within the field of waste management (logistics/business; landfill research; theoretical/consequential; waste collection problems; location/selection; monitoring/decision support systems; leachate/water contamination; waste incineration/energy production and, waste forecast/waste production behavior). Following an analysis of their content, gaps were found related to exploring the complex situations in each problem. Instead of using general rules and constraints for their methodologies to solve real-world problems, they resorted to theoretical orientation solutions. Furthermore, suggestions from specialists in the field and more fitting constraints related to the data evaluated could make the works seem less theoretical and more visually applicable. •A methodological approach focusing on algorithms and applications used by waste management researchers.•Waste management problems can be categorized into nine types of applications.•Waste collection problems are the most influential research in this niche of work.•Heuristics algorithms are the most frequently used class of methods in the selected papers.•The k-means algorithm is the most commonly used clustering technique in waste management applications. Waste management; Systematic literature review; Waste collection; Landfill location.