319 research outputs found
Efficient adaptive implementation of the serial schedule generation scheme using preprocessing and bloom filters
The majority of scheduling metaheuristics use indirect representation of solutions as a way to efficiently explore the search space. Thus, a crucial part of such metaheuristics is a “schedule generation scheme” – procedure translating the indirect solution representation into a schedule. Schedule generation scheme is used every time a new candidate solution needs to be evaluated. Being relatively slow, it eats up most of the running time of the metaheuristic and, thus, its speed plays significant role in performance of the metaheuristic. Despite its importance, little attention has been paid in the literature to efficient implementation of schedule generation schemes. We give detailed description of serial schedule generation scheme, including new improvements, and propose a new approach for speeding it up, by using Bloom filters. The results are further strengthened by automated control of parameters. Finally, we employ online algorithm selection to dynamically choose which of the two implementations to use. This hybrid approach significantly outperforms conventional implementation on a wide range of instances
Pattern backtracking algorithm for the workflow satisfiability problem with user-independent constraints
The workflow satisfiability problem (WSP) asks whether there exists an assignment of authorised users to the steps in a workflow specification, subject to certain constraints on the assignment. (Such an assignment is called valid.) The problem is NP-hard even when restricted to the large class of user-independent constraints. Since the number of steps k is relatively small in practice, it is natural to consider a parametrisation of the WSP by k. We propose a new fixed-parameter algorithm to solve the WSP with user-independent constraints. The assignments in our method are partitioned into equivalence classes such that the number of classes is exponential in k only. We show that one can decide, in polynomial time, whether there is a valid assignment in an equivalence class. By exploiting this property, our algorithm reduces the search space to the space of equivalence classes, which it browses within a backtracking framework, hence emerging as an efficient yet relatively simple-to-implement or generalise solution method. We empirically evaluate our algorithm against the state-of-the-art methods and show that it clearly wins the competition on the whole range of our test problems and significantly extends the domain of practically solvable instances of the WSP
Magneto-optical signatures of a cascade of transitions in LaBaCuO
Recent experiments in the original cuprate high temperature superconductor,
LaBaCuO, have revealed a remarkable sequence of transitions [1].
Here we investigate such crystals with Kerr effect which is sensitive to
time-reversal-symmetry breaking (TRSB). Concurrent birefringence measurements
accurately locate the structural phase transitions from high-temperature
tetragonal to low temperature orthorhombic, and then to lower temperature
tetragonal, at which temperature a strong Kerr signal onsets. Hysteretic
behavior of the Kerr signal suggests that TRSB occurs well above room
temperature, an effect that was previously observed in high quality
YBaCuO$_{6+x} crystals [2].Comment: 5 pages, 4 figure
A New Approach to Population Sizing for Memetic Algorithms: A Case Study for the Multidimensional Assignment Problem
Memetic algorithms are known to be a powerful technique in solving hard optimization problems. To design a memetic algorithm, one needs to make a host of decisions. Selecting the population size is one of the most important among them. Most of the algorithms in the literature fix the population size to a certain constant value. This reduces the algorithm's quality since the optimal population size varies for different instances, local search procedures, and runtimes. In this paper we propose an adjustable population size. It is calculated as a function of the runtime of the whole algorithm and the average runtime of the local search for the given instance. Note that in many applications the runtime of a heuristic should be limited and, therefore, we use this bound as a parameter of the algorithm. The average runtime of the local search procedure is measured during the algorithm's run. Some coefficients which are independent of the instance and the local search are to be tuned at the design time;we provide a procedure to find these coefficients. The proposed approach was used to develop a memetic algorithm for the multidimensional assignment problem (MAP). We show that our adjustable population size makes the algorithm flexible to perform efficiently for a wide range of running times and local searches and this does not require any additional tuning of the algorithm
Supernovae and their host galaxies - V. The vertical distribution of supernovae in disc galaxies
We present an analysis of the height distributions of the different types of
supernovae (SNe) from the plane of their host galaxies. We use a well-defined
sample of 102 nearby SNe appeared inside high-inclined (i > 85 deg),
morphologically non-disturbed S0-Sd host galaxies from the Sloan Digital Sky
Survey. For the first time, we show that in all the subsamples of spirals, the
vertical distribution of core-collapse (CC) SNe is about twice closer to the
plane of host disc than the distribution of SNe Ia. In Sb-Sc hosts, the
exponential scale height of CC SNe is consistent with those of the younger
stellar population in the Milky Way (MW) thin disc, while the scale height of
SNe Ia is consistent with those of the old population in the MW thick disc. We
show that the ratio of scale lengths to scale heights of the distribution of CC
SNe is consistent with those of the resolved young stars with ages from ~ 10
Myr up to ~ 100 Myr in nearby edge-on galaxies and the unresolved stellar
population of extragalactic thin discs. The corresponding ratio for SNe Ia is
consistent with the same ratios of the two populations of resolved stars with
ages from a few 100 Myr up to a few Gyr and from a few Gyr up to ~ 10 Gyr, as
well as with the unresolved population of the thick disc. These results can be
explained considering the age-scale height relation of the distribution of
stellar population and the mean age difference between Type Ia and CC SNe
progenitors.Comment: 11 pages, 6 figures, 6 tables, accepted for publication in MNRA
The impact of bars on the radial distribution of supernovae in disc galaxies
We present an analysis of the impact of bars on the radial distributions of
the different types of supernovae (SNe) in the stellar discs of host galaxies
with various morphologies. We find that in Sa-Sbc galaxies, the radial
distribution of core-collapse (CC) SNe in barred hosts is inconsistent with
that in unbarred ones, while the distributions of SNe Ia are not significantly
different. At the same time, the radial distributions of both types of SNe in
Sc-Sm galaxies are not affected by bars. We propose that the additional
mechanism shaping the distributions of Type Ia and CC SNe can be explained
within the framework of substantial suppression of massive star formation in
the radial range swept by strong bars, particularly in early-type spirals. The
radial distribution of CC SNe in unbarred Sa-Sbc galaxies is more centrally
peaked and inconsistent with that in unbarred Sc-Sm hosts, while the
distribution of SNe Ia in unbarred galaxies is not affected by host morphology.
These results can be explained by the distinct distributions of massive stars
in the discs of early-and late-type spirals.Comment: 3 pages, 1 figure. This is a brief summary of arXiv:1511.08896,
written for a short contribution in the EWASS-2016 Symposium 16 "Frontiers of
massive-star evolution and core-collapse supernovae
The horizontal profile of the atmospheric electric fields as measured during thunderstorms by the network of NaI spectrometers located on the slopes of Mt. Aragats
The International School for Advanced Studies (SISSA), find out more
paper
The horizontal profile of the atmospheric electric fields as measured during thunderstorms by the network of NaI spectrometers located on the slopes of Mt. Aragats
A. Chilingarian1, G. Hovsepyan1, T. Karapetyan1, L. Kozliner1, S. Chilingaryan1, D. Pokhsraryan1 and B. Sargsyan1
Published 6 October 2022 • © 2022 IOP Publishing Ltd and Sissa Medialab
Journal of Instrumentation, Volume 17, October 2022 Citation A. Chilingarian et al 2022 JINST 17 P10011 DOI 10.1088/1748-0221/17/10/P10011
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Abstract
The shape and evolution of the energy spectra of the thunderstorm ground enhancement (TGE) electrons and gamma rays shed light on the origin of TGEs, on the relationship between modification of the cosmic ray electron energy spectra (MOS) and relativistic runaway electron avalanche (RREA) processes, on the energy of the seed electrons, and on the strength and elongation of an atmospheric electric field. The network of large NaI spectrometers on slopes of Mt. Aragats 24/7 monitored secondary particle fluxes from 2013 until now, highly contributed to the understanding of the ways how RREAs are developed in the atmosphere. In 2022 we enlarge the NaI network with 2 remote detectors located at altitudes 2000 and 1700 m, and 13 and 16 km apart from the Aragats station to investigate the horizontal profile of the atmospheric electric field. We found, that the previously estimated values of the regions in the atmosphere, where RREA emerges, were highly underestimated. In the present report, we describe the NaI particle detector\u27s network and present the first results of the experiment demonstrating that the particle fluxes from the atmospheric electron accelerators can cover large areas on the earth\u27s (up to tens of km)
A Discrete State Transition Algorithm for Generalized Traveling Salesman Problem
Generalized traveling salesman problem (GTSP) is an extension of classical
traveling salesman problem (TSP), which is a combinatorial optimization problem
and an NP-hard problem. In this paper, an efficient discrete state transition
algorithm (DSTA) for GTSP is proposed, where a new local search operator named
\textit{K-circle}, directed by neighborhood information in space, has been
introduced to DSTA to shrink search space and strengthen search ability. A
novel robust update mechanism, restore in probability and risk in probability
(Double R-Probability), is used in our work to escape from local minima. The
proposed algorithm is tested on a set of GTSP instances. Compared with other
heuristics, experimental results have demonstrated the effectiveness and strong
adaptability of DSTA and also show that DSTA has better search ability than its
competitors.Comment: 8 pages, 1 figur
Lin-Kernighan Heuristic Adaptations for the Generalized Traveling Salesman Problem
The Lin-Kernighan heuristic is known to be one of the most successful
heuristics for the Traveling Salesman Problem (TSP). It has also proven its
efficiency in application to some other problems. In this paper we discuss
possible adaptations of TSP heuristics for the Generalized Traveling Salesman
Problem (GTSP) and focus on the case of the Lin-Kernighan algorithm. At first,
we provide an easy-to-understand description of the original Lin-Kernighan
heuristic. Then we propose several adaptations, both trivial and complicated.
Finally, we conduct a fair competition between all the variations of the
Lin-Kernighan adaptation and some other GTSP heuristics. It appears that our
adaptation of the Lin-Kernighan algorithm for the GTSP reproduces the success
of the original heuristic. Different variations of our adaptation outperform
all other heuristics in a wide range of trade-offs between solution quality and
running time, making Lin-Kernighan the state-of-the-art GTSP local search.Comment: 25 page
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