THE PARTIALLY RECHARGEABLE ELECTRIC VEHICLE ROUTING PROBLEM WITH TIME WINDOWS AND CAPACITATED CHARGING STATIONS
2015
- 1,074Usage
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Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage1,074
- Downloads926
- Abstract Views148
Thesis / Dissertation Description
Electric vehicles are potentially beneficial for both the environment and an organization's bottom line. These benefits include, but are not limited to, reduced fuel costs, government tax incentives, reduced greenhouse gas emissions, and the ability to promote a company's "green" image. In order to decide whether or not to convert or purchase electric trucks and install charging facilities, decision makers need to consider many factors including onboard battery capacity, delivery or service assignments, scheduling and routes, as well as weather and traffic conditions in a well-defined modeling framework. We develop a model to solve the partially rechargeable electric vehicle routing problem with time windows and capacitated charging stations. Given destination data and vehicle properties, our model determines the optimal number of vehicles or charging stations needed to meet the network's requirements. Analyzing the model shows the relationships between vehicle range, battery recharge time, and fleet size.
Bibliographic Details
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