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Project

Waste Logistics 4.0

This research project aims to develop a sensor and cloud based data collection framework to extract more accurate waste generation profiles on a street segment level. In a next step, this data collection framework can be used for dynamic rerouting of the waste collection fleet during operations. A second outcome of this research project is the development of a set of rich benchmark instances that are representative for waste collection problems as experienced in practice. This means that many problem constraints are active at the time (time windows, multi-trip, multi-day and multi-period, heterogeneous fleet, stochastic demand, driving time duration constraints, capacitated vehicles and intermediate processor facilities, ...). Currently, such benchmark instances are not readily available for researchers and we see this as an important outcome of this research to facilitate reproducible research in this field.
Date:13 Dec 2019 →  30 Sep 2021
Keywords:waste logistics, logistics 4.0, data mining
Disciplines:Logistics and supply chain management, Operations research and mathematical programming, Data mining