Optimal route recommendation for waste carrier vehicles for efficient waste collection: A step forward towards sustainable cities

Shabir Ahmad, Imran, Faisal Jamil, Naeem Iqbal, Do Hyeun Kim

Research output: Contribution to journalArticlepeer-review

51 Citations (Scopus)

Abstract

The exponentially growing population, urbanization, and economic development have led to the rising generation of municipal solid waste. Municipal solid waste management is thus a significant hurdle for urban societies as it consumes a large chunk of public funds, and, when mishandled, it can lead to environmental and social hazards. Some of the prerequisites required for effective waste management are the monitoring of bins, timely collection of bins, and prioritization of those areas which produce more solid waste. In this paper, we propose an optimal route recommendation system for waste carriers vehicles to effectively collect solid waste based on the profile of a particular area. This article contributes with a multi-objective optimization approach to generate a route by minimizing the route distance and maximizing the amount of waste. Then, a family of evolutionary methods is employed to solve the proposed objective function and find the optimal route for waste carrier vehicles. The experiment is carried out on the real-world solid waste data of Jeju Island, South Korea. The data is processed to predict the behavior of people of a specified grid location in terms of waste disposal. Therefore, the recommendation system caters to the predicted waste across a set of bins inside the area, and considering the constraints such as total allowed distance and time, proposes a route that is best in terms of distance (fuel consumption) and waste collection. Different use cases are illustrated to signify the proposed system, and results indicate that it can be a step forward for the implementation of smart cities, which is the goal of Jeju Island.

Original languageEnglish
Article number9068215
Pages (from-to)77875-77887
Number of pages13
JournalIEEE Access
Volume8
Early online date15 Apr 2020
DOIs
Publication statusPublished - 8 May 2020
Externally publishedYes

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