Intelligent system application in environment and waste management: A review

Abstract

Waste management issues involve uncertainties represented as intervals, random variables, and fuzzy sets related to intelligent processing. Over the last two decades, intelligent programming approaches have been increasingly developed and applied to address waste management challenges in uncertain scenarios. This paper provides an overview of recent advancements, applications, obstacles, and limitations associated with intelligent programming techniques in the context of supporting environment and waste management. The findings reveal that a majority of intelligent programming methods fall into categories high-level optimization methods, fuzzy programming, artificial neural networks, neuro-fuzzy robust, and hybrid programming. Areas demanding further research include sensitivity analysis of intelligent processing, combining intelligent programming with other modelling approaches, such as life cycle assessment, multiple-criteria decision analyses, and waste flow simulation, to promote sustainable waste management. Developing more efficient algorithms for solving the proposed methods, and establishing connections between waste management and its environmental consequences, including climate change, air pollution, greenhouse gas emissions, and leachate pollution, within an intelligent optimization framework are further areas of research in the future.