Sustainable smart waste classification and collection system: A bi-objective modeling and optimization approach

In the context of the “smart city”, information and communication technologies (ICT) have become indispensable in the planning and design of modern municipal solid waste management. Due to more waste varieties, there are urgent calls to implement waste classification worldwide, which promotes resour...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of cleaner production Jg. 276; S. 124183
Hauptverfasser: Lu, Xulong, Pu, Xujin, Han, Xiaohua
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 10.12.2020
Schlagworte:
algorithms
business enterprises
communications technology
Information and communication technologies
Multi-objective hybrid whale optimization algorithm
municipal solid waste
planning
recycling
sanitation
Smart waste classification and collection
Sustainable development
Vehicle routing problem
Information and communication technologies
Multi-objective hybrid whale optimization algorithm
Smart waste classification and collection
Sustainable development
Vehicle routing problem
ISSN:0959-6526, 1879-1786
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In the context of the “smart city”, information and communication technologies (ICT) have become indispensable in the planning and design of modern municipal solid waste management. Due to more waste varieties, there are urgent calls to implement waste classification worldwide, which promotes resource recycling to achieve sustainable development. In this paper, we present an ICT-based smart waste classification and collection system (SWCCS) that is abstracted as a bi-objective mathematical programming model to optimize the waste collection problem. To implement the proposed SWCCS effectively, we design a novel multi-objective hybrid algorithm based on the whale optimization and genetic algorithms (MOGWOA) with an improved convergence factor and a fast, non-dominated sorting method. A comparison of our algorithm with two classical multi-objective algorithms on generated test instances and on a real-world case shows that the proposed MOGWOA is more effective for optimizing the established model. This paper demonstrates how the ICT-based SWCCS works and how it can help sanitation companies improve waste collection both economically and environmentally. •A sustainable smart waste classification and collection system is investigated.•A dual-objective mathematical model is developed to minimize cost and workload.•A hybrid multi-objective whale optimization algorithm is presented.•Effectiveness of the model and algorithm proposed in this paper is proved.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2020.124183