Edges as Nodes - a New Approach to Timetable Information

In this paper we suggest a new approach to timetable information by introducing the ``edge-converted graph'' of a timetable. Using this model we present simple algorithms that solve the earliest arrival problem (EAP) and the minimum number of transfers problem (MNTP). For constant-degree graphs this yields linear-time algorithms for EAP and MNTP which improves upon the known \emph{Dijkstra}-based approaches. We also test the performance of our algorithms against the classical algorithms for EAP and MNTP in the time-expanded model

Using Incomplete Information for Complete Weight Annotation of Road Networks -- Extended Version

We are witnessing increasing interests in the effective use of road networks. For example, to enable effective vehicle routing, weighted-graph models of transportation networks are used, where the weight of an edge captures some cost associated with traversing the edge, e.g., greenhouse gas (GHG) emissions or travel time. It is a precondition to using a graph model for routing that all edges have weights. Weights that capture travel times and GHG emissions can be extracted from GPS trajectory data collected from the network. However, GPS trajectory data typically lack the coverage needed to assign weights to all edges. This paper formulates and addresses the problem of annotating all edges in a road network with travel cost based weights from a set of trips in the network that cover only a small fraction of the edges, each with an associated ground-truth travel cost. A general framework is proposed to solve the problem. Specifically, the problem is modeled as a regression problem and solved by minimizing a judiciously designed objective function that takes into account the topology of the road network. In particular, the use of weighted PageRank values of edges is explored for assigning appropriate weights to all edges, and the property of directional adjacency of edges is also taken into account to assign weights. Empirical studies with weights capturing travel time and GHG emissions on two road networks (Skagen, Denmark, and North Jutland, Denmark) offer insight into the design properties of the proposed techniques and offer evidence that the techniques are effective.Comment: This is an extended version of "Using Incomplete Information for Complete Weight Annotation of Road Networks," which is accepted for publication in IEEE TKD

Event-Driven Network Model for Space Mission Optimization with High-Thrust and Low-Thrust Spacecraft

Numerous high-thrust and low-thrust space propulsion technologies have been developed in the recent years with the goal of expanding space exploration capabilities; however, designing and optimizing a multi-mission campaign with both high-thrust and low-thrust propulsion options are challenging due to the coupling between logistics mission design and trajectory evaluation. Specifically, this computational burden arises because the deliverable mass fraction (i.e., final-to-initial mass ratio) and time of flight for low-thrust trajectories can can vary with the payload mass; thus, these trajectory metrics cannot be evaluated separately from the campaign-level mission design. To tackle this challenge, this paper develops a novel event-driven space logistics network optimization approach using mixed-integer linear programming for space campaign design. An example case of optimally designing a cislunar propellant supply chain to support multiple lunar surface access missions is used to demonstrate this new space logistics framework. The results are compared with an existing stochastic combinatorial formulation developed for incorporating low-thrust propulsion into space logistics design; our new approach provides superior results in terms of cost as well as utilization of the vehicle fleet. The event-driven space logistics network optimization method developed in this paper can trade off cost, time, and technology in an automated manner to optimally design space mission campaigns.Comment: 38 pages; 11 figures; Journal of Spacecraft and Rockets (Accepted); previous version presented at the AAS/AIAA Astrodynamics Specialist Conference, 201

An FPTAS for Quickest Multicommodity Flows with Inflow-Dependent Transit Times

Given a network with capacities and transit times on the arcs, the quickest flow problem asks for a "flow over time" that satisfies given demands within minimal time. In the setting of flows over time, flow on arcs may vary over time and the transit time of an arc is the time it takes for flow to travel through this arc. In most real-world applications (such as, e.g., road traffic, communication networks, production systems, etc.), transit times are not fixed but depend on the current flow situation in the network. We consider the model where the transit time of an arc is given as a non-decreasing function of the rate of inflow into the arc. We prove that the quickest s-t-flow problem is NP-hard in this setting and give various approximation results, including a fully polynomial time approximation scheme (FPTAS) for the quickest multicommodity flow problem with bounded cos

Mining sensor datasets with spatiotemporal neighborhoods

Many spatiotemporal data mining methods are dependent on how relationships between a spatiotemporal unit and its neighbors are defined. These relationships are often termed the neighborhood of a spatiotemporal object. The focus of this paper is the discovery of spatiotemporal neighborhoods to find automatically spatiotemporal sub-regions in a sensor dataset. This research is motivated by the need to characterize large sensor datasets like those found in oceanographic and meteorological research. The approach presented in this paper finds spatiotemporal neighborhoods in sensor datasets by combining an agglomerative method to create temporal intervals and a graph-based method to find spatial neighborhoods within each temporal interval. These methods were tested on real-world datasets including (a) sea surface temperature data from the Tropical Atmospheric Ocean Project (TAO) array in the Equatorial Pacific Ocean and (b) NEXRAD precipitation data from the Hydro-NEXRAD system. The results were evaluated based on known patterns of the phenomenon being measured. Furthermore the results were quantified by performing hypothesis testing to establish the statistical significance using Monte Carlo simulations. The approach was also compared with existing approaches using validation metrics namely spatial autocorrelation and temporal interval dissimilarity. The results of these experiments show that our approach indeed identifies highly refined spatiotemporal neighborhoods

The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations

Multi-agent simulation has increasingly been used for transportation simulation in recent years. With current techniques, it is possible to simulate systems consisting of several million agents. Such multi-agent simulations have been applied to whole cities and even large regions. In this paper it is demonstrated how to adapt an existing multi-agent transportation simulation framework to large-scale pedestrian evacuation simulation. The underlying flow model simulates the traffic-based on a simple queue model where only free speed, bottleneck capacities, and space constraints are taken into account. The queue simulation, albeit simple, captures the most important aspects of evacuations such as the congestion effects of bottlenecks and the time needed to evacuate the endangered area. In the case of an evacuation simulation the network has time-dependent attributes. For instance, large-scale inundations or conflagrations do not cover all the endangered area at once. These time-dependent attributes are modeled as network change events. Network change events are modifying link parameters at predefined points in time. The simulation framework is demonstrated through a case study for the Indonesian city of Padang, which faces a high risk of being inundated by a tsunami.BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIENBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacitie

Περί κοινωνιοκεντρικών προσεγγίσεων στο πρόβλημα δρομολόγησης σε ασύρματα οπορτουνιστικά δίκτυα

Τα τελευταία χρόνια, το ενδιαφέρον της δρομολόγησης στα οπορτουνιστικά δίκτυα επικεντρώνεται στην εξαγωγή των κοινωνικών χαρακτηριστικών που θα μπορούσαν να περιγράψουν τα συγκεκριμένα δίκτυα. Κάποιες μετρικές κεντρικότητας, όπως το Betweenness Centrality, που αντιστοιχεί στο βαθμό που ένας κόμβος βρίσκεται στη διαδρομή που συνδέει άλλους κόμβους, παρουσιάζουν τη σπουδαιότητα κάθε κόμβου στην αναμετάδοση ενός μηνύματος προς κάποιον προορισμό, συνεισφέροντας σε μία καλύτερη δρομολόγηση, συγκριτικά με τις πιο απλοϊκές τεχνικές. Ωστόσο, η ανωτέρω προσέγγιση παρουσιάζει τρεις αδυναμίες: α) Η δρομολόγηση είναι ανεξάρτητη του προορισμού του μηνύματος. β) Η απόδοση καθορίζεται άμεσα από το γράφο των επαφών μεταξύ των κόμβων, στους οποίους υπολογίζονται οι τιμές κεντρικότητας. γ) Η συνολική κεντρικότητα του δικτύου πρέπει πρακτικά να υπολογιστεί με χρήση των εγωκεντρικών δικτύων. Η παρούσα εργασία εξετάζει πειραματικά την επίδραση αυτών των τριών παραγόντων στη δρομολόγηση που εκμεταλλεύεται την κεντρικότητα. Πέντε διαφορετικές τεχνικές δρομολόγησης συγκρίνονται μεταξύ τους και με δύο εξαιρετικές περιπτώσεις πολύπλοκης δρομολόγησης στα DTN: το απλό πρωτόκολλο δρομολόγησης με πιθανότητες και ένα ιδεατό σχήμα, με πλήρη γνώση των μελλοντικών επαφών, που υπολογίζει τη βέλτιστη χωροχρονική διαδρομή σε έναν πρωτότυπο γράφο, με κόμβους τις επαφές και ακμές με χρονικά βάρη. Τα αποτελέσματα αποδεικνύουν ότι η δρομολόγηση με βάση την κεντρικότητα περικλείει εγγενείς αδυναμίες.The exploitation of social context for routing data in opportunistic networks is a relatively recent trend. Node centrality metrics, such as the betweenness centrality, quantify the relaying utility of network nodes and inform routing decisions,resulting in better performance than more naive routing approaches. Nevertheless, centrality-based routing is far from optimal for three main reasons: a) routing decisions are greedy and message destination-agnostic; b) its performance is highly sensitive to the contact graph over which the node centrality values are computed; c) the global network centrality values have for practical reasons to be approximated by their egocentric counterparts. Our paper experimentally assesses the impact of these three factors on the efficacy of centrality-based routing. Five centrality-based routing variants are compared with each other and against two schemes representing extreme instances of DTN routing complexity:the simple probabilistic forwarding protocol and an ideal scheme with perfect knowledge of future contacts that computes optimal message space-time paths over a novel graph construct with contacts as vertices and time-weighted edges.The results of this comparison are not always inline with intuition and indicate inherent weaknesses of centrality-based routing