This paper presents an exact algorithm for the single machine total tardiness problem (1//SigmaT(i)). We present a new synthesis of various results from the literature which leads to a compact and concise representati...
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This paper presents an exact algorithm for the single machine total tardiness problem (1//SigmaT(i)). We present a new synthesis of various results from the literature which leads to a compact and concise representation of job precedences, a simple optimality check, new decomposition theory, a new lower bound, and a check for presolved subproblems. These are integrated through the use of an equivalence concept that permits a continuous reformation of the data to permit early detection of optimality at the nodes of an enumeration tree. The overall effect is a significant reduction in the size of the search tree, CPU times, and storage requirements. The algorithm is capable of handling much larger problems (e.g., 500 jobs) than its predecessors in the literature (less than or equal to 150). In addition, a simple modification of the algorithm gives a new heuristic which significantly outperforms the best known heuristics in the literature.
The planning of offshore oil or gas field infrastructure under uncertainty is addressed in this article. The main uncertainties considered are in the initial maximum oil or gas flowrate, the recoverable oil or gas vol...
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The planning of offshore oil or gas field infrastructure under uncertainty is addressed in this article. The main uncertainties considered are in the initial maximum oil or gas flowrate, the recoverable oil or gas volume, and the water breakthrough time of the reservoir, which are represented by discrete distributions. Furthermore, it is assumed that these uncertainties are not immediately realized, but are gradually revealed as a function of design and operation decisions. To account for these decision-dependent uncertainties, we propose a multistage stochastic programming model that captures the complex economic objectives and nonlinear reservoir behavior and simultaneously optimizes the investment and operating decisions over the entire planning horizon. The proposed solution algorithm relies on a duality-based branch-and-bound method involving subproblems as nonconvex mixed-integer nonlinear programs. Several examples involving nonlinear reservoir models are presented to illustrate the application of the proposed method.
The authors present a local stereo matching algorithm whose performance is insensitive to changes in radiometric conditions between the input images. First, a prior on the disparities is built by combining the DAISY d...
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The authors present a local stereo matching algorithm whose performance is insensitive to changes in radiometric conditions between the input images. First, a prior on the disparities is built by combining the DAISY descriptor and Census filtering. Then, a Census-based cost aggregation with a self-adaptive window is performed. Finally, the maximum a-posteriori estimation is carried out to compute the disparity. The authors' algorithm is compared with both local and global stereo matching algorithms (NLCA, ELAS, ANCC, Adapt Weight and CSBP) by using Middlebury datasets. The results show that the proposed algorithm achieves high-accuracy dense disparity estimations and is more robust to radiometric differences between input images than other algorithms.
A new algorithm for iterative blind image restoration is presented in this paper. The method extends blind equalization found in the signal case to the image. A neural network blind equalization algorithm is derived a...
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A new algorithm for iterative blind image restoration is presented in this paper. The method extends blind equalization found in the signal case to the image. A neural network blind equalization algorithm is derived and used in conjunction with Zigzag coding to restore the original image. As a result, the effect of PSF can be removed by using the proposed algorithm, which contributes to eliminate intersymbol interference (ISI). In order to obtain the estimation of the original image, what is proposed in this method is to optimize constant modulus blind equalization cost function applied to grayscale CT image by using conjugate gradient method. Analysis of convergence performance of the algorithm verifies the feasibility of this method theoretically;meanwhile, simulation results and performance evaluations of recent image quality metrics are provided to assess the effectiveness of the proposed method.
A novel hydraulic fracture (HF) formulation is introduced which accounts for the hydraulically induced shear stress at the crack faces. It utilizes a general form of the elasticity operator alongside a revised fractur...
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A novel hydraulic fracture (HF) formulation is introduced which accounts for the hydraulically induced shear stress at the crack faces. It utilizes a general form of the elasticity operator alongside a revised fracture propagation condition based on the critical value of the energy release rate. It is shown that the revised formulation describes the underlying physics of HF in a more accurate way and is in agreement with the asymptotic behaviour of the linear elastic fracture mechanics. A number of numerical simulations by means of the universal HF algorithm previously developed in [Wrobel M., Mishuris G. (2015) Hydraulic fracture revisited: Particle velocity based simulation. International Journal of Engineering Science, 94: 23-58] are performed in order to: (i) compare the modified HF formulation with its classic counterpart and (ii) investigate the peculiarities of the former. Computational advantages of the revised HF model are demonstrated. Asymptotic estimations of the main solution elements are provided for the cases of small and large toughness. The modified formulation opens new ways to analyse the physical phenomenon of HF and also improves the reliability and efficiency of its numerical simulations. (C) 2016 Elsevier Ltd. All rights reserved.
We present an approximate method of performing the Fourier transform of the data sampled in nonequidistant readouts. It is shown that the data can be recalculated as equidistant readouts by using a nonuniform convolut...
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We present an approximate method of performing the Fourier transform of the data sampled in nonequidistant readouts. It is shown that the data can be recalculated as equidistant readouts by using a nonuniform convolution, i.e., convolution of a certain function whose form depends on the calculated element and the character of nonequidistance. Thus, this recalculation does not require calculation of the values of the initial data in intermediate readouts (unlike the linear approximation, spline, or other recalculations). Since the size of the kernel of this nonuniform convolution is about 9, the proposed method can be the basis for an efficient computational algorithm. Applicability of the proposed approach to spectral optical coherence tomography is demonstrated.
High-flying unmanned aerial vehicles (UAVs) are transforming industrial and research agriculture by delivering high spatiotemporal resolution data on a field environment. While current UAVs fly high above fields colle...
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High-flying unmanned aerial vehicles (UAVs) are transforming industrial and research agriculture by delivering high spatiotemporal resolution data on a field environment. While current UAVs fly high above fields collecting aerial imagery, future low-flying aircraft will directly interact with the environment and will utilize a wider variety of sensors. Safely and reliably operating close to unstructured environments requires improving UAVs' sensing, localization, and control algorithms. To this end, we investigate localizing a micro-UAV in corn phenotyping trials using a laser scanner and IMU to control the altitude and position of the vehicle relative to the plant rows. In this process, the laser scanner is not only a means of localization, but also a scientific instrument for measuring plant properties. Experimental evaluations demonstrate that the is capable of safely and reliably operating in real-world phenotyping trials. We experimentally validate the system in both low and high wind conditions in fully mature corn fields. Using test data from 18 test flights, we show that the UAV is capable of localizing its position to within one field row of the true position. (C) 2017 Wiley Periodicals, Inc.
A two-dimensional inverse transient heat conduction algorithm is developed to estimate the heat flux and convection heat transfer coefficient on the bottom (top) surface of the multilayered functionally graded (FG) ci...
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A two-dimensional inverse transient heat conduction algorithm is developed to estimate the heat flux and convection heat transfer coefficient on the bottom (top) surface of the multilayered functionally graded (FG) circular plates using the measured temperature on their top (bottom) surface. The non-Fourier heat transfer, in conjunction with the layerwise-incremental differential quadrature method (LW-IDQM), is employed to accurately model the problem. The conjugate gradient method (CGM), coupled with the sensitivity and adjoint problems, are employed for the optimization procedure. The reliability and robustness of the presented approach is demonstrated by simulating the exact and noisy data through different examples.
The conventional interacting multiple model (IMM) algorithm will increase the computational load when applying a large number of models, meanwhile, it cannot yield accurate estimation results with a small number of mo...
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The conventional interacting multiple model (IMM) algorithm will increase the computational load when applying a large number of models, meanwhile, it cannot yield accurate estimation results with a small number of models. Furthermore, the unknown target acceleration is regarded as an additional process noise to the target model, and its time-varying variance is hard to be approximated. The paper proposes a fuzzy-logic adaptive variable structure multiple model (FAVSMM) algorithm for tracking a high maneuvering target. The algorithm can optimize the model parameters using the model probability and construct an optimal model set quickly, and the fuzzy-logic IMM algorithm included in the FAVSMM algorithm is adopted for states estimation. The simulation results show that the proposed algorithm can match well with the actual target trajectory with less computational complexity and better accuracy. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
In this paper, an unstructured Chimera mesh method is used to compute incompressible flow around a rotating body. To implement the pressure correction algorithm on unstructured overlapping sub-grids, a novel interpola...
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In this paper, an unstructured Chimera mesh method is used to compute incompressible flow around a rotating body. To implement the pressure correction algorithm on unstructured overlapping sub-grids, a novel interpolation scheme for pressure correction is proposed. This indirect interpolation scheme can ensure a tight coupling of pressure between sub-domains. A moving-mesh finite volume approach is used to treat the rotating sub-domain and the governing equations are formulated in an inertial reference frame. Since the mesh that surrounds the rotating body undergoes only solid body rotation and the background mesh remains stationary, no mesh deformation is encountered in the computation. As a benefit from the utilization of an inertial frame, tensorial transformation for velocity is not needed. Three numerical simulations are successfully performed. They include flow over a fixed circular cylinder, flow over a rotating circular cylinder and flow over a rotating elliptic cylinder. These numerical examples demonstrate the capability of the current scheme in handling moving boundaries. The numerical results are in good agreement with experimental and computational data in literature. (C) 2007 Elsevier Ltd. All rights reserved.
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