A Novel Hybrid Optimization Algorithm of Pattern Search and IWO

2014 ◽  
Vol 687-691 ◽  
pp. 1557-1559
Author(s):  
Hui Hui Xiao
Keyword(s):  
Optimization Algorithm ◽  
Search Algorithm ◽  
Pattern Search ◽  
Hybrid Optimization ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Intelligent Optimization ◽  
Hybrid Optimization Algorithm ◽  
Simulation Results ◽  
Swarm Intelligence Algorithm

Invasive weed optimization algorithm is a new swarm intelligence algorithm recently. The algorithm has better robustness and adaptation, which is a very good intelligent optimization tools; but it is easy to fall into local optimization, and having the low speed of convergence, and it can not acquire exactly. Aiming at the shortcomings of the algorithm, taking advantage of pattern search excellent local search ability, this paper presents a novel hybrid optimization algorithm of pattern search algorithm and IWO optimization. The Simulation results of three standard benchmark functions show that the improved algorithm can greatly improve the convergence precision and convergence speed, and can effectively discourage the premature convergence.

Derivative-Free Hybrid Optimization Method for Top Design of Satellite System

2011 ◽  
Vol 308-310 ◽  
pp. 2413-2417
Author(s):  
Ying Guo Chen ◽  
Shuai Lu ◽  
Xiao Lu Liu ◽  
Ying Wu Chen
Keyword(s):  
Optimization Algorithm ◽  
Gaussian Processes ◽  
Design Space ◽  
Optimization Method ◽  
Satellite System ◽  
Pattern Search ◽  
Hybrid Optimization ◽  
Hybrid Optimization Algorithm ◽  
Hybrid Optimization Method ◽  
Derivative Free

This paper combines a derivative-free hybrid optimization algorithm, generalize pattern search (GPS), with Treed Gaussian Processes (TGP) to create a new hybrid optimization algorithm. The goal is to use the method for top design of satellite system, in which the objective or constraint functions usually are computationally expensive black-box functions. TGP model partitions the design space into disjoint regions, and employs independent Gaussian Processes (GP) in each partition to represent the time consumption of true problem responses. Utilizing the TGP, we generate the new “promising” points, which are the combination of model-predicted values and estimated model errors. Then, these points are used to guide GPS search in the design space efficiently. The hybrid optimization method is applied to top design of multi-satellites cooperated observation. The results demonstrate that the proposed method can not only increase the chance of obtaining optimal solution but also cut down the cost of function evaluations.

scholarly journals Seismic Analysis of Earth Slope Using a Novel Sequential Hybrid Optimization Algorithm

2022 ◽  
Author(s):  
Mohammad Khajehzadeh ◽  
Suraparb Keawsawasvong ◽  
Payam Sarir ◽  
Dlshad Khurshid Khailany
Keyword(s):  
Stability Analysis ◽  
Slope Stability ◽  
Optimization Algorithm ◽  
Seismic Analysis ◽  
Slope Stability Analysis ◽  
Pattern Search ◽  
Hybrid Optimization ◽  
Seismic Slope Stability ◽  
Hybrid Optimization Algorithm ◽  
Earth Slope

One of the most important topics in geotechnical engineering is seismic analysis of the earth slope. In this study, a pseudo-static limit equilibrium approach is applied for the slope stability evaluation under earthquake loading based on the Morgenstern–Price method for the general shape of the slip surface. In this approach, the minimum factor of safety corresponding to the critical failure surface should be investigated and it is a complex optimization problem. This paper proposed an effective sequential hybrid optimization algorithm based on the tunicate swarm algorithm (TSA) and pattern search (PS) for seismic slope stability analysis. The proposed method employs the global search ability of TSA and the local search ability of PS. The performance of the new CTSA-PS algorithm is investigated using a set of benchmark test functions and the results are compared with the standard TSA and some other methods from the literature. In addition, two case studies from the literature are considered to evaluate the efficiency of the proposed CTSA-PS for seismic slope stability analysis. The numerical investigations show that the new approach may provide better optimal solutions and outperform previous methods.

scholarly journals Cardiac Stroke Prediction Framework using Hybrid Optimization Algorithm under DNN

2021 ◽  
Vol 11 (4) ◽  
pp. 7436-7441
Author(s):  
N. K. Al-Shammari ◽  
A. A. Alzamil ◽  
M. Albadarn ◽  
S. A. Ahmed ◽  
M. B. Syed ◽  
...  
Keyword(s):  
Blood Flow ◽  
Optimization Algorithm ◽  
Missing Values ◽  
Search Algorithm ◽  
High Accuracy ◽  
Hybrid Optimization ◽  
Air Bubbles ◽  
Hybrid Optimization Algorithm ◽  
Whale Optimization ◽  
Detailed Evaluation

Heart weakness and restricted blood flow into the cavities can cause a range of strokes from mild to severe Heart strokes are primary caused due to the fat deposited on artery walls. The process reduces the intake of blood and internally causes a pseudo vacuum of air bubbles leading to a stroke which can be identified with high-end instrumentations. In this article, a detailed evaluation is processed with a Hybrid Optimization Algorithm (HOA). In the proposed technique, data are preprocessed using a label encoder and the missing values of the dataset are filled. Whale Optimization Algorithm (WOA) and Crow Search Algorithm(CSA) extract inter-connected patterns and learning features using a dedicated Deep Neural Networking (DNN) support. The proposed Hybrid Optimization Algorithm extracts features and the resultant values demonstrate a high accuracy range of 97.34%.

Convergence Analysis of Hybrid Free Search and Invasive Weed Optimization Algorithm

2011 ◽  
Vol 143-144 ◽  
pp. 329-334
Author(s):  
Lu Li ◽  
Xing Yu Wang ◽  
Zi Hou Zhang ◽  
Liu Bin Fan
Keyword(s):  
Continuous Function ◽  
Optimization Algorithm ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Function Optimization ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Late Evolution ◽  
Hybrid Intelligence ◽  
Free Search

Considering the fitness of each individual, a hybrid intelligence algorithm is established, which combine the excellent probing ability of free search algorithm (FS) with exploiting ability of invasive weed optimization algorithm (IWO). The hybrid algorithm can overcome the disadvantage of lower optimization rate in late evolution for FS and taking advantage of powerful exploiting abilities for IWO. Identity between FS and IWO is analyzed and convergence of the two algorithms in solving continuous function optimization is provided. Simulations confirmed the analysis. Multi-model Shubert function is chosen to carry out the simulation. Compared with FS and IWO, the hybrid algorithm is superior in convergence speed and robustness.

Optimization Design of Drawbead in Drawing Tools of Autobody Cover Panel

2002 ◽  
Vol 124 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Gang Liu ◽  
Zhongqin Lin ◽  
Youxia Bao
Keyword(s):  
Optimization Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Experimental Results ◽  
Hybrid Optimization ◽  
Force Model ◽  
Hybrid Optimization Algorithm ◽  
Design Plan ◽  
Formed Part ◽  
Restraining Force

In the tooling design of autobody cover panels, design of drawbead will affect the distribution of drawing restraining force along mouth of dies and the relative flowing velocity of the blank, and consequently, will affect the distributions of strain and thickness in a formed part. Therefore, reasonable design of drawbead is the key point of cover panels’ forming quality. An optimization design method of drawbead, using one improved hybrid optimization algorithm combined with FEM software, is proposed in this paper. First, we used this method to design the distribution of drawbead restraining force along the mouth of a die, then the actual type and geometrical parameters of drawbead could be obtained according to an improved drawbead restraining force model and the improved hybrid optimization algorithm. This optimization method of drawbead was used in designing drawing tools of an actual autobody cover panel, and an optimized drawbead design plan has been obtained, by which deformation redundancy was increased from 0% under uniform drawbead control to 10%. Plastic strain of all area of formed part was larger than 2% and the minimum flange width was larger than 10 mm. Therefore, not only better formability and high dent resistance were obtained, but also fine cutting contour line and high assembly quality could be obtained. An actual drawing part has been formed using the optimized drawbead, and the experimental results were compared with the simulating results in order to verify the validity of the optimized design plan. Good agreement of thickness on critical areas between experimental results and simulation results proves that the optimization design method of drawbead could be successfully applied in designing actual tools of autobody cover panels.

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