114 research outputs found
Hierarchical Cut Labelling -- Scaling Up Distance Queries on Road Networks
Answering the shortest-path distance between two arbitrary locations is a
fundamental problem in road networks. Labelling-based solutions are the current
state-of-the-arts to render fast response time, which can generally be
categorised into hub-based labellings, highway-based labellings, and tree
decomposition labellings. Hub-based and highway-based labellings exploit
hierarchical structures of road networks with the aim to reduce labelling size
for improving query efficiency. However, these solutions still result in large
search spaces on distance labels at query time, particularly when road networks
are large. Tree decomposition labellings leverage a hierarchy of vertices to
reduce search spaces over distance labels at query time, but such a hierarchy
is generated using tree decomposition techniques, which may yield very large
labelling sizes and slow querying. In this paper, we propose a novel solution
\emph{hierarchical cut 2-hop labelling (HC2L)} to address the drawbacks of the
existing works. Our solution combines the benefits of hierarchical structures
from both perspectives - reduce the size of a distance labelling at
preprocessing time and further reduce the search space on a distance labelling
at query time. At its core, we propose a new hierarchy, \emph{balanced tree
hierarchy}, which enables a fast, efficient data structure to reduce the size
of distance labelling and to select a very small subset of labels to compute
the shortest-path distance at query time. To speed up the construction process
of HC2L, we further propose a parallel variant of our method, namely HC2L.
We have evaluated our solution on 10 large real-world road networks through
extensive experiments
Recent Advances in Fully Dynamic Graph Algorithms
In recent years, significant advances have been made in the design and
analysis of fully dynamic algorithms. However, these theoretical results have
received very little attention from the practical perspective. Few of the
algorithms are implemented and tested on real datasets, and their practical
potential is far from understood. Here, we present a quick reference guide to
recent engineering and theory results in the area of fully dynamic graph
algorithms
Algorithm Engineering for Realistic Journey Planning in Transportation Networks
Diese Dissertation beschäftigt sich mit der Routenplanung in Transportnetzen. Es werden neue, effiziente algorithmische Ansätze zur Berechnung optimaler Verbindungen in öffentlichen Verkehrsnetzen, Straßennetzen und multimodalen Netzen, die verschiedene Transportmodi miteinander verknüpfen, eingeführt. Im Fokus der Arbeit steht dabei die Praktikabilität der Ansätze, was durch eine ausführliche experimentelle Evaluation belegt wird
Reallocating Multiple Facilities on the Line
We study the multistage -facility reallocation problem on the real line,
where we maintain facility locations over stages, based on the
stage-dependent locations of agents. Each agent is connected to the nearest
facility at each stage, and the facilities may move from one stage to another,
to accommodate different agent locations. The objective is to minimize the
connection cost of the agents plus the total moving cost of the facilities,
over all stages. -facility reallocation was introduced by de Keijzer and
Wojtczak, where they mostly focused on the special case of a single facility.
Using an LP-based approach, we present a polynomial time algorithm that
computes the optimal solution for any number of facilities. We also consider
online -facility reallocation, where the algorithm becomes aware of agent
locations in a stage-by-stage fashion. By exploiting an interesting connection
to the classical -server problem, we present a constant-competitive
algorithm for facilities
Recommended from our members
Text Indexing for Long Patterns: Anchors are All you Need
PVLDB Artifact Availability:
The source code, data, and/or other artifacts have been made available at https://github.com/lorrainea/BDA- index.Copyright © 2023 the owner/author(s). In many real-world database systems, a large fraction of the data is represented by strings: sequences of letters over some alphabet. This is because strings can easily encode data arising from different sources. It is often crucial to represent such string datasets in a compact form but also to simultaneously enable fast pattern matching queries. This is the classic text indexing problem. The four absolute measures anyone should pay attention to when designing or implementing a text index are: (i) index space; (ii) query time; (iii) construction space; and (iv) construction time. Unfortunately, however, most (if not all) widely-used indexes (e.g., suffix tree, suffix array, or their compressed counterparts) are not optimized for all four measures simultaneously, as it is difficult to have the best of all four worlds. Here, we take an important step in this direction by showing that text indexing with locally consistent anchors (lc-anchors) offers remarkably good performance in all four measures, when we have at hand a lower bound l on the length of the queried patterns --- which is arguably a quite reasonable assumption in practical applications. Specifically, we improve on the construction of the index proposed by Loukides and Pissis, which is based on bidirectional string anchors (bd-anchors), a new type of lc-anchors, by: (i) designing an average-case linear-time algorithm to compute bd-anchors; and (ii) developing a semi-external-memory implementation to construct the index in small space using near-optimal work. We then present an extensive experimental evaluation, based on the four measures, using real benchmark datasets. The results show that, for long patterns, the index constructed using our improved algorithms compares favorably to all classic indexes: (compressed) suffix tree; (compressed) suffix array; and the FM-index.European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No 872539 and 956229, respectively; and by UKRI through REPHRAIN (EP/V011189/1)
Solving the p-Median Problem with Insights from Discrete Vector Quantization
The goals of this paper are twofold. First, we formally equate the p-median problem from facility location to the optimal design of a vector quantizer. Second, we use the equivalence to show that the Maranzana Algorithm can be interpreted as a projected Lloyd Algorithm, a fact that improves complexity. Numerical results verify significant improvements in run-time
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