1,720,959 research outputs found

    Dynamic routing for the Electric Vehicle Shortest Path Problem with charging station occupancy information

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    We study the problem of an Electric Vehicle (EV) having to travel from an origin to a destination in the shortest amount of time. We focus on long-distance settings, where the shortest path between the origin and the destination has energy requirements exceeding the EV autonomy. The EV may charge its battery at public Charging Stations (CSs), which are subject to unknown arrivals of exogenous vehicles requiring uncertain charging times. Thus, the waiting times at CSs are uncertain. Similar to other contributions in the literature, we model CSs using appropriately defined queues, whose status is revealed upon the EV arrival. However, following recent technological advances, we also consider that the status of each CS is updated in real-time via binary Occupancy Indicator (OI) information signaling if a CS is busy or not. Therefore, we assume that the EV continuously receives OI updates on all CSs. At each update, we determine the sequence of CSs to visit along with associated charging quantities. We name the resulting problem as the Electric Vehicle Shortest Path Problem with charging station Occupancy Indicator information (EVSPP-OI). In this problem, we consider that the EV is allowed to partially charge its battery, and we model charging times via piecewise linear charging functions that depend on the CS technology.We propose a Markov Decision Process formulation for the EVSPP-OI, which aims at optimizing the EV routing and charging policy. To solve the problem, we develop a reoptimization algorithm that establishes the sequence of CS visits and charging amounts based on system updates. Specifically, we propose a simulation-based approach to estimate the waiting time of the EV at a CS as a function of its arrival time. As the path to a CS may consist of multiple intermediate CS stops, estimating the arrival times at each CS is fairly intricate. To this end, we propose an efficient heuristic that yields approximate lower bounds on the arrival time of the EV at each CS, which are used to derive an estimation of the waiting time at each CS. We use these estimations to define a compatible deterministic version of the EVSPP, which we solve with an existing algorithm. We conduct a comprehensive computational study and compare the performance of our methodology with a benchmark that observes the status of CSs only upon arrival (i.e., with no OI information). Results show that our method reduces waiting times and total trip duration by an average of 23.7%-95.4% and 1.4%-18.5%, respectively

    Off-line approximate dynamic programming for the vehicle routing problem with a highly variable customer basis and stochastic demands

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    We study a stochastic variant of the vehicle routing problem (VRP) arising in the context of domestic donor collection services. The problem we consider combines the following attributes. Customers requesting services are variable, in the sense that they are stochastic, but are not restricted to a predefined set. Furthermore, demand volumes are also stochastic and are observed upon visiting customers. The objective is to maximize the expected served demands while meeting vehicle capacity and time restrictions. We call this problem the VRP with a highly Variable Customer basis and Stochastic Demands (VRP-VCSD). We first propose a classical Markov Decision Process (MDP) formulation for the VRP-VCSD. The resulting model is, however, unusable due to the explosion in the dimension of the state and action spaces.To solve the VRP-VCSD, we propose a number of methodological contributions aimed at reducing the state and action spaces. We first reformulate the MDP as an MDP with a consecutive action selection procedure. In this formulation, we enforce the treatment of a single vehicle (as opposed to multiple vehicles) at each decision epoch. We then introduce an observation function that selects a subset of the available information, which is deemed relevant for the considered vehicle in each epoch. We develop a Q-learning algorithm called QN-CO. In particular, we use a continuous state representation and incorporate a two-layer artificial neural network to approximate the Q values. Furthermore, we propose an aggregation strategy yielding a fixed-size output. Finally, we enhance our algorithm with Replay Memory and a Double Q Network.We conduct a thorough computational analysis. Results show that QN-CO considerably outperforms five benchmark policies. Moreover, we show that QN-CO can compete with specialized methods developed for the particular case of the VRP-VCSD where customer locations and expected demands are known in advance

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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