scholarly journals A fast two-point gradient algorithm based on sequential subspace optimization method for nonlinear ill-posed problems

2021 ◽  
Author(s):  
Guangyu Gao ◽  
Bo Han ◽  
Shanshan Tong
Keyword(s):  
Optimization Method ◽  
Gradient Algorithm ◽  
Subspace Optimization ◽  
Ill Posed

scholarly journals Heating source localization in a reduced time

2016 ◽  
Vol 26 (3) ◽  
pp. 623-640 ◽  
Author(s):  
Sara Beddiaf ◽  
Laurent Autrique ◽  
Laetitia Perez ◽  
Jean-Claude Jolly
Keyword(s):  
Heat Conduction ◽  
Source Localization ◽  
Conjugate Gradient ◽  
Regularization Method ◽  
Three Dimensional ◽  
Gradient Algorithm ◽  
Iterative Regularization ◽  
Heating Source ◽  
Ill Posed ◽  
Reduced Time

Abstract Inverse three-dimensional heat conduction problems devoted to heating source localization are ill posed. Identification can be performed using an iterative regularization method based on the conjugate gradient algorithm. Such a method is usually implemented off-line, taking into account observations (temperature measurements, for example). However, in a practical context, if the source has to be located as fast as possible (e.g., for diagnosis), the observation horizon has to be reduced. To this end, several configurations are detailed and effects of noisy observations are investigated.

scholarly journals Optimization Algorithm for Lifetime of Mobile Wireless Sensor Networks Based on Grid

2019 ◽  
Vol 15 (01) ◽  
pp. 44
Author(s):  
Ren Song
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Control Method ◽  
Optimization Method ◽  
Gradient Algorithm ◽  
Wireless Sensor ◽  
Premature Failure ◽  
Method Optimization ◽  
Mobile Wireless Sensor ◽  
Node Energy

To avoid premature failure due to excessive energy consumption of some nodes in the network, the node energy consumption problem was considered. Network life was maximized. For the problem of node energy consumption, multiple methods such as the shortest path method, optimization method, and power control method were used to solve the problem of optimization of the survival time of the wireless sensor network in different scenarios and improve the network lifetime. The results showed that the sub-gradient algorithm could balance the node energy consumption and the number of neighbor nodes and extend the maximum network lifetime. Therefore, under certain conditions, the algorithm is better than the algorithm using fixed transmission power.

scholarly journals Reconstruction of Electrical Impedance Tomography Using Fish School Search, Non-Blind Search, and Genetic Algorithm

2017 ◽  
Vol 8 (2) ◽  
pp. 17-33 ◽  
Author(s):  
Valter A. F. Barbosa ◽  
Reiga R. Ribeiro ◽  
Allan R. S. Feitosa ◽  
Victor L. B. A. Silva ◽  
Arthur D. D. Rocha ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Imaging Technique ◽  
Optimization Method ◽  
Impedance Tomography ◽  
Circular Section ◽  
Fish School ◽  
Noninvasive Imaging Technique ◽  
Ill Posed ◽  
Blind Search

Electrical Impedance Tomography (EIT) is a noninvasive imaging technique that does not use ionizing radiation, with application both in environmental sciences and in health. Image reconstruction is performed by solving an inverse problem and ill-posed. Evolutionary Computation and Swarm Intelligence have become a source of methods for solving inverse problems. Fish School Search (FSS) is a promising search and optimization method, based on the dynamics of schools of fish. In this article the authors present a method for reconstruction of EIT images based on FSS and Non-Blind Search (NBS). The method was evaluated using numerical phantoms consisting of electrical conductivity images with subjects in the center, between the center and the edge and on the edge of a circular section, with meshes of 415 finite elements. The authors performed 20 simulations for each configuration. Results showed that both FSS and FSS-NBS were able to converge faster than genetic algorithms.

Optimal Design of a Mechanism Used for Opening and Shutting a Ship’s Hatch Cover

1984 ◽  
Vol 106 (4) ◽  
pp. 503-509
Author(s):  
Koichi Ito ◽  
Tadashi Kuroiwa ◽  
Shinsuke Akagi
Keyword(s):  
Optimal Design ◽  
Nonlinear Optimization ◽  
Optimization Problem ◽  
Numerical Study ◽  
Optimal Solution ◽  
Optimization Method ◽  
Gradient Algorithm ◽  
Linkage Mechanism ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

A nonlinear optimization method is proposed to design a linkage mechanism used for opening and shutting a ship’s hatch cover. Considering the maximum force of the oil cylinder necessary to move the hatch cover as the objective function to be minimized, the design problem to determine the optimal configuration of linkage mechanism is formulated as a nonlinear optimization problem of minimax type. It it shown that the optimal solution can be derived by adopting the generalized reduced gradient algorithm together with a linkage statical simulation model, and the effectiveness of the algorithm is ascertained through a numerical study.

The Truss Structural Optimization Design Based on Improved Hybrid Genetic Algorithm

2010 ◽  
Vol 163-167 ◽  
pp. 2304-2308
Author(s):  
Feng Guo Jiang ◽  
Zhen Qing Wang
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Structural Optimization ◽  
Optimization Design ◽  
Hybrid Genetic Algorithm ◽  
Optimization Method ◽  
Gradient Algorithm ◽  
General Search ◽  
Genetic Arithmetic ◽  
Iteration Analysis

Genetic arithmetic operators in genetic algorithm be improved , and a hybrid genetic algorithm of a gradient algorithm combining with the genetic algorithm be given against to the defects such as premature，slow on convergence rate，weak in the ability of local search ，all these appeared on the progress of genetic algorithm's iteration. Analysis result indicate that not only strong on the local search capacity of gradient algorithm be exhibited but also strong on the general search capacity of genetic algorithm be combined based on the hybrid genetic algorithm ,which make phenomenon of premature avoid, and the rate of convergence be improved greatly. Concrete calculated example indicated that the hybrid genetic algorithm is an effective structural optimization method.

An Inverse Method Using a Genetic Algorithm to Determine Spatial Temperature Distribution From Infrared Tranmissivity Measurements in a Gas

Volume 4 ◽  
2004 ◽  
Author(s):  
Keith A. Woodbury ◽  
Courtney Graham ◽  
John Baker ◽  
Charles Karr
Keyword(s):  
Genetic Algorithm ◽  
Temperature Distribution ◽  
Inverse Problems ◽  
Inverse Method ◽  
Biological Evolution ◽  
Optimization Method ◽  
Global Optimum ◽  
Simple Problem ◽  
Straight Line ◽  
Ill Posed

The ill-posed nature of inverse problems suggests that a solution be obtained through an optimization method. Genetic algorithms (GAs) effectively locate the global optimum, and are therefore an appealing technique to solve inverse problems. GAs mimic biological evolution, refining a set of solutions until the best solution is found. In this report, a genetic algorithm is developed and demonstrated based on a simple problem of determining the equation of a straight line. Then the GA is modified and implemented to estimate the temperature distribution in a gas based on the measured infrared tranmissivity distribution. The ulitimate task of this inverse method will be determination of the gas composition based on these transmissivity measurements.

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