Waste Collection Based on a Real Time Route Planning System
The WSmart Route project aims to explore a new paradigm that relies on smart waste management, where real time data plays a central role in changing the way operations are managed today, moving from a static to dynamic routes definition. The tool to be developed will integrate technology with management concerns contributing to improve the companies’ operations decision-making process.
Based on the team’s experience in static waste collection optimization and on preliminary results obtained from seminal studies on dynamic waste collection, it is estimated that the usage of a planning tool like the one proposed should lower companies’ operational costs around 35% and increase their kg/km ratio by 40%.
The present project proposes an innovative tool for smart waste management aiming to improve the quality of the operational decisions in the waste collection business. To achieve such goal, the aim of this research project is to:
- Given the volumetric sensors in use by one of the project’s partners, validate the accuracy of the data measured and define the requirements, in terms of information, needed for the real time route planning tool;
- Develop and test a planning tool based on new mathematical models and state-of-the-art solution methods to define dynamic optimal routes considering the data provided by the sensors and accounting for the issues above mentioned;
- Assess the benefits of the real time route planning tool and develop a cost-benefit analysis comparing the as-is to the to-be situation in a real case study.
Considering the above stated objectives, the project will encompass four main tasks: technology and information management, mathematical models development for Waste-TOP, solution methods exploration, and benefit analysis.
Figure 1 - Synthesis of the project's main tasks and their interaction.
The first task, technology and information management, aims at gathering data from the waste containers in order to acertain their filling rate. In the images bellow, is represented the installation of measurement sensors, the platform used for data monitoring and, at last, the comparison between sensor readings and manual registrations.
Figure 2 - Installation of sensors, after the selection of the test containers and their preparation.
Figure 3 - Data monitoring software and the deviations between manual and seonsor readings.
The second phase consisted in the development of mathematical models for waste collection. For this, four different approaches were taken. These approaches are schematized in figure 3. From this work phase a paper was published Ramos T. R. P., Morais, C. S., & Barbosa-Póvoa, A. P. (2018). The smart waste collection routing problem: Alternative operational management approaches. Expert Systems with Applications.
Figure 4 - Schematic of the four approaches taken for the development of mathematical model for waste collection.
The third task of this project consists on the development of solution methods for the waste collection. For this, a simulated annealing algorithm was developed. In the following video the results for the simulated annealing with an instance of 226 bins with route distance balancing are shown.
At last, the final task, benefit analysis, aims at testing our solution method in a real case - our partner ERSUC, and assessing the benefits of using the sensors, performing a cost-benefit analysis.
If you wish to learn more about this project please refer to the website link in the banner, or click here.
