7 resultados para Vehicle Departure Model

em Aston University Research Archive


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Purpose – This paper aims to provide a critical comment on complex funding systems. Design/methodology/approach – This is a critical comment written in the form of a poem. The poem is in the style of the English light opera composers Gilbert and Sullivan, and is a variation on their song “I Am the Very Model of a Modern Major General”, from The Pirates of Penzance. Findings - The poem spotlights financial failure. Originality/value - The poem spotlights the crazy names and poor transparency of special purpose vehicles.

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Neural stem cells (NSC) are a valuable model system for understanding the intrinsic and extrinsic controls for self-renewal and differentiation choice. They also offer a platform for drug screening and neurotoxicity studies, and hold promise for cell replacement therapies for the treatment of neurodegenerative diseases. Fully exploiting the potential of this experimental tool often requires the manipulation of intrinsic cues of interest using transfection methods, to which NSC are relatively resistant. In this paper, we show that mouse and human NSC readily take up polystyrene-based microspheres which can be loaded with a range of chemical or biological cargoes. This uptake can take place in the undifferentiated stage without affecting NSC proliferation and their capacity to give rise to neurons and glia. We demonstrate that ß-galactosidase-loaded microspheres could be efficiently introduced into NSC with no apparent toxic effect, thus providing proof-of-concept for the use of microspheres as an alternative biomolecule delivery system.

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This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

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We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.

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Local air quality was one of the main stimulants for low carbon vehicle development during the 1990s. Issues of national fuel security and global air quality (climate change) have added pressure for their development, stimulating schemes to facilitate their deployment in the UK. In this case study, Coventry City Council aimed to adopt an in-house fleet of electric and hybrid-electric vehicles to replace business mileage paid for in employee's private vehicles. This study made comparisons between the proposed vehicle technologies, in terms of costs and air quality, over projected scenarios of typical use. The study found that under 2009 conditions, the electric and hybrid fleet could not compete on cost with the current business model because of untested assumptions, but certain emissions were significantly reduced >50%. Climate change gas emissions were most drastically reduced where electric vehicles were adopted because the electricity supply was generated by renewable energy sources. The study identified the key cost barriers and benefits to adoption of low-emission vehicles in current conditions in the Coventry fleet. Low-emission vehicles achieved significant air pollution-associated health cost and atmospheric emission reductions per vehicle, and widespread adoption in cities could deliver significant change. © The Author 2011. Published by Oxford University Press. All rights reserved.

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Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.