Development of semi-adaptive Waste Collection Vehicle Routing Algorithm for agglomeration and urban settlements

Dolinina, Olga; Pechenkin, Vitaly; Gubin, Nikolay; Aizups, Janis; Kuzmin, Alexey

doi:10.1109/aieee48629.2019.8976918

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…The authors also included environmental aspects in the proposed model. Dolinina et al [53] propose a mathematical model for rerouting in a solid waste collection system, while Puspita et al [54] use an open capacitation VRP. An SWM is studied by Gdowska et al [12] from another perspective.…”

Section: Recent Advances In Decision Support Systems For Solid Waste Managementmentioning

confidence: 99%

Recyclables Collection Route Balancing Problem with Heterogeneous Fleet

2021

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Nowadays, robust and efficient solid waste collection is crucial to motivate citizens to participate in the circular economy by sorting recyclable solid waste. Vocational vehicles, including garbage trucks, contribute significantly to CO2 emissions; therefore, it is strongly recommended, and in the European Union it is mandatory, to replace conventional-fuel-based garbage trucks with electric ones. For providing sustainable and energy-efficient solid waste collection with a heterogeneous fleet, in-depth mathematical computations are needed to support solving complex decision-making problems, including crew rostering and vehicle routing, because the distance and capacity of electric garbage trucks differ from conventional-fuel-based ones. However, the literature on solid waste collection using electric garbage trucks is still relatively scarce. The main contribution of this paper is developing an optimization problem for balancing travel distance assigned to each garbage truck of a heterogeneous fleet. The problem is based on specific requirements of the Municipal Solid Waste Management in Cracow, Poland, where the working time of routes is balanced and the total time of collection service can be minimized. For the problem, an MIP program was developed to generate optimal crew schedules, so that the hitherto network of segregated solid waste pickup nodes can be served using a heterogeneous fleet in which the share of electric garbage trucks is up to 30%. We study the impact of the changed composition of the fleet on modifications in crew rostering due to the shorter range of an electric vehicle compared to a conventional-fuel-based one.

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Section: Recent Advances In Decision Support Systems For Solid Waste Managementmentioning

confidence: 99%

Recyclables Collection Route Balancing Problem with Heterogeneous Fleet

2021

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“…As such, they develop a heuristic method for planning waste collection routes, using a WSN able to raise a set of alarms to initiate/trigger waste collection. The research presented by Dolinina, Pechenkin, Gubin, Aizups and Kuzmin (2019), on the other hand, uses the IoT and smart measuring devices to create a waste collection tool and promote its integration in a smart city environment. The authors claim that Intelligent Transport Systems (ITS) allow making efficient routing and avoid traffic congestion.…”

Section: (I) Waste Managementmentioning

confidence: 99%

“…In three of these 11 studies, roadside data are used together with other data sources (e.g., vehicles data sources). (Bespalov et al, 2017) x (Anagnosto et al, 2018) x (Burger et al, 2018) x (Gazder et al, 2018) x (Teja et al, 2018) x (Rosa-Gallardo et al, 2018) x (Omara et al, 2018) x (Dolinina et al, 2019) x (Bharathi et al, 2019) x x (Medehal et al, 2020) x x (Malky et al, 2020…”

Section: Data Sourcesmentioning

confidence: 99%

“…In both cases, the authors underline the valuable results obtained and the need for further testing. Moreover, Pufahl et al (2020) conduct a pilot study for six months in a German city of 300k inhabitants, Anagnostopoulos et al (2018) validated their system on an experiment held in the Saint Petersburg (Russia), Burger et al (2018) tested their solution in the German city of Regensburg, involving biological waste and more than 800 waste containers, the system proposed by Dolinina et al (2019) has been tested in Saratov (Russia), with results showing a 21% decrease in the processing time of containers compared to traditional manual planning and, finally, Alwabli et al (2020) conducted an experiment in Alawali District in Mecca with 52 waste collection points.…”

Section: Maturity Levelmentioning

confidence: 99%

“…Combining fill-level sensing with route optimization for a more efficient waste collection. Dolinina, O. et al (2019). Development of semi-adaptive waste collection vehicle routing algorithm for agglomeration and urban settlements.…”

Section: Improvement Of the Last Mile Logisticsmentioning

confidence: 99%

See 2 more Smart Citations

Smart cities and urban logistics: a systematic review of the literature

et al. 2022

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The concept of smart cities is seen as a key strategy to mitigate the problems generated by the rapid urbanization. Within the smart cities umbrella, the so-called smart mobility has been subject of considerable research. The systematic review reported by this article aimed to identify the most relevant applications supported by smart cities’ infrastructure with an impact in urban logistic transports. A total of 39 articles were retrieved, and the results show that the main application areas are related to solid waste management and the routing of logistic fleets, namely, to improve the last mile logistics.

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