An electric vehicle routing problem with charging time and variable travel time is developed to address some operational issues such as range limitation and charging demand. The model is solved by using genetic algorithm to obtain the routes, the vehicle departure time at the depot, and the charging plan. Meanwhile, a dynamic Dijkstra algorithm is applied to find the shortest path between any two adjacent nodes along the routes. To prevent the depletion of all battery power and ensure safe operation in transit, electric vehicles with insufficient battery power can be repeatedly recharged at charging stations. The fluctuations in travel time are implemented to reflect a dynamic traffic environment. In conclusion, a large and realistic case study with a road network in the Beijing urban area is conducted to evaluate the model performance and the solution technology and analyze the results.
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Background Although pneumonia is a leading cause of death in New York City (NYC), limited data exist about the settings in which pneumonia ...
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Summary We tested whether prophylactic droperidol and ondansetron, in combination with a moderate dose of dexamethasone, were equally effe...
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by Demin Li, Carol Bentley, Jenna Yates, Maryam Salimi, Jenny Greig, Sarah Wiblin, Tasneem Hassanali, Alison H. Banham Therapeutic monoclon...
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ACS Nano DOI: 10.1021/acsnano.6b08567 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2oNpdhD via...
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Abstract Dermoscopy has demonstrated clinical benefits in improving early melanoma diagnosis and reducing unnecessary biopsies. Despite th...
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