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Charging Type Selection for Electric Buses Using Interval-Valued Neutrosophic Decision Support Model

Using electricity to fuel buses has always been known as a green option for the public bus operations considering the recent regulations on environmental and climate concerns. Emission-free public transportation modes such as electric buses improve local air quality and reduce noise pollution and also contribute to achieving sustainability goals by developing a sustainable transportation system. Many projects have been carried out using different charging strategies for electric buses around the world. However, selecting the most appropriate charging strategy for the electric buses in the public transportation is a challenging and multidimensional decision-making problem for transportation management sector. Therefore, this article proposes a decision support model based on the interval-valued neutrosophic set which uses Shannon's entropy and mixed aggregation by comprehensive normalization technique to choose the most appropriate charging type for urban electric buses among alternatives such as opportunity, depot, inductive, and no shift. This article presents a real-life case study in Turkey to illustrate the applicability and advantages of the proposed model. Extensive sensitivity analysis and comparative analysis tests are conducted to show the robustness of the proposed methodology. The results show that depot charging is the most suitable charging strategy for Istanbul's bus operator system.
- RWTH Aachen University Germany
- Naval Academy Turkey
- Naval Academy Turkey
- Sabancı University Turkey
- National Defence University Pakistan
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).19 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
