Fuzzy vehicle routing problem for a municipal solid waste management system with greenhouse gas emission at various disposal stages

In developing countries, municipal solid waste management and their authorities face hurdles during the collection, transport, trash segregation process, and disposal of solid waste that will have an environmental impact and affect human health and the economy. This study investigates an existing case study of the waste management system, and the existing case study mainly focuses on determining the routes and clusters within each ward for weekdays and weekends by utilizing the Clarke and Wright algorithm. The availability of daily waste is increasing due to the real-life consequences of dry leaves, household garbage, contaminated material waste, digging waste, etc. Therefore, the availability of daily garbage for each ward is considered fuzzy. This study examines garbage collection from the main region of each ward to the transfer station to the processing plant for weekdays and weekend periods and also addresses greenhouse gas emissions from various disposal stages of the waste management system under an uncertain environment. In this paper, the cluster-first-route-second approach is used to minimize the total travel distance and emission for the fuzzy waste management vehicle routing problem. The Variant Fisher and Jaikumar algorithm and the Sweep algorithm with the Nearest Neighbor algorithm are used to solve this problem. A comparative analysis has been demonstrated between these two algorithms, showing that the Variant Fisher and Jaikumar algorithm with the nearest neighbor algorithm provides the optimal clusters, routes, and minimum distance with the lowest emission value. This approach to urban waste management improves sustainable practices throughout the disposal network.