scholarly journals Smoothness preserving layout for dynamic labels by hybrid optimization

2021 ◽  
Vol 8 (1) ◽  
pp. 149-163
Author(s):  
Yu He ◽  
Guo-Dong Zhao ◽  
Song-Hai Zhang
Keyword(s):  
Global Optimization ◽  
High Speed ◽  
Optimization Methods ◽  
Optimization Method ◽  
Streaming Data ◽  
Resultant Force ◽  
Hybrid Optimization ◽  
Global Optimization Method ◽  
Trade Off ◽  
Global Optimization Methods

AbstractStable label movement and smooth label trajectory are critical for effective information understanding. Sudden label changes cannot be avoided by whatever forced directed methods due to the unreliability of resultant force or global optimization methods due to the complex trade-off on the different aspects. To solve this problem, we proposed a hybrid optimization method by taking advantages of the merits of both approaches. We first detect the spatial-temporal intersection regions from whole trajectories of the features, and initialize the layout by optimization in decreasing order by the number of the involved features. The label movements between the spatial-temporal intersection regions are determined by force directed methods. To cope with some features with high speed relative to neighbors, we introduced a force from future, called temporal force, so that the labels of related features can elude ahead of time and retain smooth movements. We also proposed a strategy by optimizing the label layout to predict the trajectories of features so that such global optimization method can be applied to streaming data.

A New Global Optimization Method for Simultaneous Computation on Expensive Black-Box Functions

2003 ◽  
Author(s):  
Liqun Wang ◽  
Songqing Shan ◽  
G. Gary Wang
Keyword(s):  
Global Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Global Optimum ◽  
Black Box ◽  
Efficient Global Optimization ◽  
Global Optimization Method ◽  
Global Optimization Methods

The presence of black-box functions in engineering design, which are usually computation-intensive, demands efficient global optimization methods. This work proposes a new global optimization method for black-box functions. The global optimization method is based on a novel mode-pursuing sampling (MPS) method which systematically generates more sample points in the neighborhood of the function mode while statistically covers the entire search space. Quadratic regression is performed to detect the region containing the global optimum. The sampling and detection process iterates until the global optimum is obtained. Through intensive testing, this method is found to be effective, efficient, robust, and applicable to both continuous and discontinuous functions. It supports simultaneous computation and applies to both unconstrained and constrained optimization problems. Because it does not call any existing global optimization tool, it can be used as a standalone global optimization method for inexpensive problems as well. Limitation of the method is also identified and discussed.

scholarly journals Calibration of the modified Bartlett-Lewis model using global optimization techniques and alternative objective functions

2012 ◽  
Vol 16 (3) ◽  
pp. 873-891 ◽  
Author(s):  
W. J. Vanhaute ◽  
S. Vandenberghe ◽  
K. Scheerlinck ◽  
B. De Baets ◽  
N. E. C. Verhoest
Keyword(s):  
Global Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Objective Functions ◽  
Local Search Algorithms ◽  
Stochastic Point Process ◽  
Shuffled Complex Evolution ◽  
Global Optimization Methods ◽  
Downhill Simplex

Abstract. The calibration of stochastic point process rainfall models, such as of the Bartlett-Lewis type, suffers from the presence of multiple local minima which local search algorithms usually fail to avoid. To meet this shortcoming, four relatively new global optimization methods are presented and tested for their ability to calibrate the Modified Bartlett-Lewis Model. The list of tested methods consists of: the Downhill Simplex Method, Simplex-Simulated Annealing, Particle Swarm Optimization and Shuffled Complex Evolution. The parameters of these algorithms are first optimized to ensure optimal performance, after which they are used for calibration of the Modified Bartlett-Lewis model. Furthermore, this paper addresses the choice of weights in the objective function. Three alternative weighing methods are compared to determine whether or not simulation results (obtained after calibration with the best optimization method) are influenced by the choice of weights.

scholarly journals Calibration of the modified Bartlett-Lewis model using global optimization techniques and alternative objective functions

2011 ◽  
Vol 8 (6) ◽  
pp. 9707-9756 ◽  
Author(s):  
W. J. Vanhaute ◽  
S. Vandenberghe ◽  
K. Scheerlinck ◽  
B. De Baets ◽  
N. E. C. Verhoest
Keyword(s):  
Time Series ◽  
Global Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Rainfall Time Series ◽  
Stochastic Point Process ◽  
Shuffled Complex Evolution ◽  
Global Optimization Methods ◽  
Downhill Simplex

Abstract. The use of rainfall time series for various applications is widespread. However, in many cases historical rainfall records lack in length or quality for certain practical purposes, resulting in a reliance on rainfall models to supply simulated rainfall time series, e.g., in the design of hydraulic structures. One way to obtain such simulations is by means of stochastic point process rainfall models, such as the Bartlett-Lewis type of model. It is widely acknowledged that the calibration of such models suffers from the presence of multiple local minima which local search algorithms usually fail to avoid. To meet this shortcoming, four relatively new global optimization methods are presented and tested for their abilities to calibrate the Modified Bartlett-Lewis Model (MBL). The list of tested methods consists of: the Downhill Simplex Method (DSM), Simplex-Simulated Annealing (SIMPSA), Particle Swarm Optimization (PSO) and Shuffled Complex Evolution (SCE-UA). The parameters of these algorithms are first optimized to ensure optimal performance, after which they are used for calibration of the MBL model. Furthermore, this paper addresses the issue of subjectivity in the choice of weights in the objective function. Three alternative weighing methods are compared to determine whether or not simulation results (obtained after calibration with the best optimization method) are influenced by the choice of weights.

scholarly journals A Global Optimization Method to Determine the Complex Material Constants of Piezoelectric Bars in the Length Thickness Extensional Mode

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 169
Author(s):  
Xiangming Xiong ◽  
Xiaotian Li
Keyword(s):  
Global Optimization ◽  
Piezoelectric Materials ◽  
Optimization Methods ◽  
Optimization Method ◽  
Dielectric Constants ◽  
Impedance Spectra ◽  
Global Optimization Method ◽  
Material Constants ◽  
The Difference ◽  
Optimal Material

Optimization methods have been used to determine the elastic, piezoelectric, and dielectric constants of piezoelectric materials from admittance or impedance measurements. The optimal material constants minimize the difference between the modeled and measured admittance or impedance spectra. In this paper, a global optimization method is proposed to calculate the optimal material constants of piezoelectric bars in the length thickness extensional mode. The algorithm is applied to a soft PZT and a hard PZT and is shown to be robust.

scholarly journals Facility location via continuous optimization with discontinuous objective functions

2007 ◽  
Vol 48 (3) ◽  
pp. 315-325 ◽  
Author(s):  
J. Ugon ◽  
S. Kouhbor ◽  
M. Mammadov ◽  
A. Rubinov ◽  
A. Kruger
Keyword(s):  
Global Optimization ◽  
Facility Location ◽  
Continuous Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Location Problems ◽  
Objective Functions ◽  
Global Optimization Method ◽  
Facility Location Problems ◽  
Real World Application

AbstractFacility location problems are one of the most common applications of optimization methods. Continuous formulations are usually more accurate, but often result in complex problems that cannot be solved using traditional optimization methods. This paper examines theuse of a global optimization method—AGOP—for solving location problems where the objective function is discontinuous. This approach is motivated by a real-world application in wireless networks design.

CAN GLOBAL OPTIMIZATION TECHNIQUE COMPENSATE FOR MARKER SKIN MOVEMENT IN RAT KINEMATICS?

2014 ◽  
Vol 14 (05) ◽  
pp. 1450065 ◽  
Author(s):  
FILIPA JOÃO ◽  
ANTÓNIO VELOSO ◽  
SANDRA AMADO ◽  
PAULO ARMADA-DA-SILVA ◽  
ANA C. MAURÍCIO
Keyword(s):  
Global Optimization ◽  
Optimization Technique ◽  
Three Dimensional ◽  
Optimization Methods ◽  
Optimization Method ◽  
Anatomical Landmarks ◽  
Global Optimization Method ◽  
Skin Deformation ◽  
Angular Displacements ◽  
The Right

The motion of the skeletal estimated from skin attached marker-based motion capture(MOCAP) systems is known to be affected by significant bias caused by anatomical landmarks mislocation but especially by soft tissue artifacts (such as skin deformation and sliding, inertial effects and muscle contraction). As a consequence, the error associated with this bias can propagate to joint kinematics and kinetics data, particularly in small rodents. The purpose of this study was to perform a segmental kinematic analysis of the rat hindlimb during locomotion, using both global optimization as well as segmental optimization methods. Eight rats were evaluated for natural overground walking and motion of the right hindlimb was captured with an optoeletronic system while the animals walked in the track. Three-dimensional (3D) biomechanical analyses were carried out and hip, knee and ankle joint angular displacements and velocities were calculated. Comparison between both methods demonstrated that the magnitude of the kinematic error due to skin movement increases in the segmental optimization when compared with the global optimization method. The kinematic results assessed with the global optimization method matches more closely to the joint angles and ranges of motion calculated from bone-derived kinematics, being the knee and hip joints with more significant differences.

scholarly journals Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm

2021 ◽  
Author(s):  
Felix Neumann ◽  
Johannes T Margraf ◽  
Karsten Reuter ◽  
Albert Bruix
Keyword(s):  
Global Optimization ◽  
Bimetallic Nanoparticles ◽  
Optimization Methods ◽  
Trade Off ◽  
Energy Trade ◽  
Global Optimization Methods ◽  
The Stability ◽  
Symmetric Structures ◽  
Shape Changes ◽  
Stable Shape

Despite the large relevance of bimetallic metal nanoparticles for heterogeneous catalysis, the relation between their shape and elemental composition remains elusive. Here, we investigate this relationship by implementing and applying global optimization methods enhanced with a novel optimal-exchange algorithm. In particular, we determine the lowest energy chemical orderings for PtAu nanoparticles, revealing that the most stable shape changes from highly symmetric structures for pure particles to distorted and less symmetric shapes for intermediate compositions. The presented method leverages the local atomic contributions to an empirical surrogate energy expression to identify optimal atom exchanges. This also allows us to pinpoint the origin of the stability of distorted shapes, revealing a favorable energy trade-off when over-coordinating Pt and under-coordinating Au upon distorting the particle shape.

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