Dynamic urban solid waste management system for smart cities
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Adriano Silva was supported by FCT-MIT Portugal PhD
grant SFRH/BD/151346/2021, and Thadeu Brito was supported by FCT PhD
grant SFRH/BD/08598/2020. This work was financially supported by UIDB/057
57/2020 (CeDRI), UIDB/00690/2020 (CIMO), LA/P/0045/2020 (ALiCE), UID
B/500 20/2020, UI- DP/50020/2020 (LSRE-LCM) and funded by national funds
through FCT/MCTES (PIDDAC). Jose L. Diaz de Tuesta acknowledges the
finantial support through the program of Atraccion de Talento of Atraccion al
Talento of the Comunidad de Madrid (Spain) for the individual research grant
2020-T2/AMB-19836.
Increasing population in cities combined with efforts to ob tain more sustainable living spaces will require a smarter Solid Waste
Management System (SWMS). A critical step in SWMS is the collection
of wastes, generally associated with expensive costs faced by companies
or municipalities in this sector. Some studies are being developed for the
optimization of waste collection routes, but few consider inland cities as
model regions. Here, the model region considered for the route optimiza tion using Guided Local Search (GLS) algorithm was Bragança, a city
in the northeast region of Portugal. The algorithm used in this work is
available in open-source Google OR-tools. Results show that waste col lection efficiency is affected by the upper limit of waste in dumpsters.
Additionally, it is demonstrated the importance of dynamic selection of
dumpsters. For instance, efficiency decreased 10.67% for the best upper
limit compared to the traditional collection in the regular selection of
dumpsters (levels only). However, an improvement of 50.45% compared
to traditional collection was observed using dynamic selection of dump sters to be collected. In other words, collection cannot be improved only
by letting dumpsters reach 90% of waste level. In fact, strategies such as
the dynamic selection here presented, can play an important role to save
resources in a SWMS.
