Search results for "Benchmark"
showing 10 items of 310 documents
Trends in multiple recurrent health complaints in 15-year-olds in 35 countries in Europe, North America and Israel from 1994 to 2010
2015
Background: Health complaints are a good indicator of an individual’s psychosocial health and well-being. Studies have shown that children and adolescents report health complaints which can cause significant individual burden. Methods: Using data from the international Health Behaviour in School-aged Children study, this article describes trends in multiple recurrent health complaints (MHC) in 35 countries among N = 237 136 fifteen-year-olds from 1994 to 2010. MHC was defined as the presence of two or more health complaints at least once a week. Logistic regression analysis was performed to evaluate trends across the five survey cycles for each country. Results: Lowest prevalence thro…
On the generalized directed rural postman problem
2014
The generalized directed rural postman problem (GDRPP) is a generic type of arc routing problem. In the present paper, it is described how many types of practically relevant single-vehicle routing problems can be modelled as GDRPPs. This demonstrates the versatility of the GDRPP and its importance as a unified model for postman problems. In addition, an exact and a heuristic solution method are presented. Computational experiments using two large sets of benchmark instances are performed. The results show high solution quality and thus demonstrate the practical usefulness of the approach.
Which Is Which? Evaluation of Local Descriptors for Image Matching in Real-World Scenarios
2019
Matching with local image descriptors is a fundamental task in many computer vision applications. This paper describes the WISW contest held within the framework of the CAIP 2019 conference, aimed at benchmarking recent descriptors in challenging planar and non-planar real image matching scenarios. According to the contest results, the descriptors submitted to the competition, most of which based on deep learning, perform significantly better than the current state-of-the-art in image matching. Nonetheless, there is still room for improvement, especially in the case of non-planar scenes.
Monte Carlo calculation of dose rate distributions around 0.5 and 0.6 mm in diameter 192Ir wires
1999
Monte Carlo simulations of absolute dose rate in liquid water are presented in the form of away-along tables for 1 and 5 cm 192 Ir wires of 0.5 and 0.6 mm diameter. Simulated absolute dose rate values can be used as benchmark data to verify the calculation results of treatment planning systems or directly as input data for treatment planning. Best fit value of an attenuation coefficient suitable for use in Sievert integral-type calculations has been derived based on Monte Carlo simulation results. For the treatment planning systems that are based on the TG43 formalism we have also computed the required dosimetry parameters.
On Constraint Handling in Surrogate-Assisted Evolutionary Many-Objective Optimization
2016
Surrogate-assisted evolutionary multiobjective optimization algorithms are often used to solve computationally expensive problems. But their efficacy on handling constrained optimization problems having more than three objectives has not been widely studied. Particularly the issue of how feasible and infeasible solutions are handled in generating a data set for training a surrogate has not received much attention. In this paper, we use a recently proposed Kriging-assisted evolutionary algorithm for many-objective optimization and investigate the effect of infeasible solutions on the performance of the surrogates. We assume that constraint functions are computationally inexpensive and consid…
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
2005
This paper surveys the research on the metaheuristics for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval; all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. Metaheuristics are general solution procedures that explore the solution space to identify good solutions and often embed some of the standard route construction and improvemen…
Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms
2005
This paper presents a survey of the research on the vehicle routing problem with time windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval, all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. Both traditional heuristic route construction methods and recent local search algorithms are examined. The basic features of each method are described, and experimental results for Solom…
Improving Performance of Evolutionary Algorithms with Application to Fuzzy Control of Truck Backer-Upper System
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/709027 Open access We propose a method to improve the performance of evolutionary algorithms (EA). The proposed approach defines operators which can modify the performance of EA, including Levy distribution function as a strategy parameters adaptation, calculating mean point for finding proper region of breeding offspring, and shifting strategy parameters to change the sequence of these parameters. Thereafter, a set of benchmark cost functions is utilized to compare the results of the proposed method with some other well-known algorithms.…
Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach
2021
This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results obtained with the novel approach to those obtained with previously used approaches. We show that the novel approach guarantees the feasibility and robust efficiency of the produced solutions under all selected scenarios, while decreasing computation cost, addresses the scenario-dependency issues, and enables the decision-makers to explore the trade-off …
Geometric optimal control of the contrast problem in Magnetic Resonance Imaging
2012
Abstract The control of the dynamics of spin systems by magnetic fields has opened intriguing possibilities in quantum computing and in Nuclear Magnetic Resonance spectroscopy. In this framework, optimal control theory has been used to design control fields able to realize a given task while minimizing a prescribed cost such as the energy of the field or the duration of the process. However, some of the powerful tools of optimal control had not been used yet for NMR applications in medical imagery. Here, we show that the geometric control theory approach can be advantageously combined with NMR methods to crucially optimize the imaging contrast. This approach is applied to a benchmark proble…