Multivariant Optimization Algorithm with Absorption for Multimodal Optimization

2013 ◽  
Vol 483 ◽  
pp. 458-464 ◽  
Author(s):  
Chang Xing Gou ◽  
Xin Ling Shi ◽  
Bao Lei Li ◽  
Tian Song Li ◽  
Ya Jie Liu ◽  
...  
Keyword(s):  
Success Rate ◽  
Optimization Algorithm ◽  
Experimental Results ◽  
High Success Rate ◽  
Multimodal Optimization ◽  
Group Property ◽  
Absorption Mechanism ◽  
Global Optima ◽  
Search Information ◽  
Improved Algorithm

Multivariant Optimization Algorithm (MOA) is a newly proposed algorithm and its multi-group property make it a perfect choice for multimodal optimization. In this paper, an absorption mechanism was introduced into MOA to remove the redundant search information that stored in the structure and we named the proposed algorithm as the Absorption Multivariant Optimization Algorithm (AMOA). With this mechanism, more search information will be captured and the search information will be shared more effectively. The proposed algorithm is tested on nine benchmark functions to compare the performance with standard MOA under the same condition. The experimental results suggest that the improved algorithm can keep high success rate as the number of global optima increase and the output result would be more stable.

Process-Monitor’s Multimodal Optimization with Dynamic Cloning Based Immune Network Algorithm

2013 ◽  
Vol 662 ◽  
pp. 781-787 ◽  
Author(s):  
Yu Guang Zhu ◽  
Xu Hua Shi ◽  
Xiong Yang ◽  
Li Xiang Shen
Keyword(s):  
Process Monitoring ◽  
Optimization Algorithm ◽  
Numerical Optimization ◽  
Experimental Results ◽  
Immune Network ◽  
Search Performance ◽  
Multimodal Optimization ◽  
Global Numerical Optimization ◽  
Network Mechanism ◽  
Process Monitor

A novel process-monitor multimodal optimization algorithm, called Pmdcopt-aiNet is given. It is based on biological immune network mechanism for process-monitor global-numerical optimization. The Pmdcopt-aiNet models can clone the process-monitor operation using dynamic cloning operation which is adopted from biological immune network mechanism. The experiments based on the multimodal benchmarks were carried out to compare the performance of Pmdcopt-aiNet with that of other existing algorithms. The experimental results in process monitoring show that the new algorithm is capable of improving search performance significantly in successful rate and convergence speed when compared with the already existing method.

Multivariant Optimization Algorithm for Multimodal Optimization

2013 ◽  
Vol 483 ◽  
pp. 453-457 ◽  
Author(s):  
Bao Lei Li ◽  
Xin Ling Shi ◽  
Chang Xing Gou ◽  
Tian Song Li ◽  
Ya Jie Liu ◽  
...  
Keyword(s):  
Local Search ◽  
Success Rate ◽  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Multimodal Optimization ◽  
Multimodal Functions

In this paper, a heuristic Multivariant Optimization Algorithm (MOA), which has the ability to locate multiple optima through alternating global-local search iterations by multivariant search groups including global exploration groups and local exploitation groups based on a structure where the optimizing process is saved, is described in detail. The performances of MOA are compared with that of other heuristic algorithms including GA and PSO based on six benchmark functions and the experiment results indicate that MOA outperforms GA and PSO in success rate and convergence efficiency on multimodal functions.

scholarly journals Remote English Teaching Resource Sharing Based on Internet O2O Model

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
ZuoXun Hou
Keyword(s):  
Success Rate ◽  
Resource Sharing ◽  
Transmission Efficiency ◽  
Communication Cost ◽  
Experimental Results ◽  
High Success Rate ◽  
Low Latency ◽  
English Teaching ◽  
Teaching Resource ◽  
Resource Substitution

Aiming at the problems of low success rate, delay, and high communication cost in distance English teaching resource sharing, this paper puts forward a method of distance English teaching resource sharing based on Internet O2O mode. Based on the model of distance English teaching resource sharing, this paper designs four processes: query, reply, resource substitution, and resource sharing optimization. Experimental results show that the proposed method can achieve high success rate of resource sharing, low latency, communication cost, and high transmission efficiency. Therefore, it is an effective method.

An Alternative to High-Temperature and Acid/Solvent-Based Methods for Removing Integrated Circuits from Ceramic or Other Problem Substrates

2005 ◽  
Author(s):  
Carl M. Nail
Keyword(s):  
High Temperature ◽  
Integrated Circuits ◽  
Success Rate ◽  
Mechanical Damage ◽  
Test Equipment ◽  
High Success Rate ◽  
Automated Test Equipment ◽  
Removal Method ◽  
Automated Test ◽  
Conventional Methods

Abstract Dice must often be removed from their packages and reassembled into more suitable packages for them to be tested in automated test equipment (ATE). Removing bare dice from their substrates using conventional methods poses risks for chemical, thermal, and/or mechanical damage. A new removal method is offered using metallography-based and parallel polishing-based techniques to remove the substrate while exposing the die to minimized risk for damage. This method has been tested and found to have a high success rate once the techniques are learned.

scholarly journals Multimodal Optimization of Permutation Flow-Shop Scheduling Problems Using A Clustering-Genetic-Algorithm-Based Approach

2021 ◽  
Vol 11 (8) ◽  
pp. 3388
Author(s):  
Pan Zou ◽  
Manik Rajora ◽  
Steven Y. Liang
Keyword(s):  
Genetic Algorithm ◽  
Clustering Algorithm ◽  
Flow Shop ◽  
Optimal Schedule ◽  
Flow Shop Scheduling ◽  
Multimodal Optimization ◽  
Shop Scheduling ◽  
Permutation Flow Shop Scheduling ◽  
Permutation Flow Shop ◽  
Global Optima

Though many techniques were proposed for the optimization of Permutation Flow-Shop Scheduling Problem (PFSSP), current techniques only provide a single optimal schedule. Therefore, a new algorithm is proposed, by combining the k-means clustering algorithm and Genetic Algorithm (GA), for the multimodal optimization of PFSSP. In the proposed algorithm, the k-means clustering algorithm is first utilized to cluster the individuals of every generation into different clusters, based on some machine-sequence-related features. Next, the operators of GA are applied to the individuals belonging to the same cluster to find multiple global optima. Unlike standard GA, where all individuals belong to the same cluster, in the proposed approach, these are split into multiple clusters and the crossover operator is restricted to the individuals belonging to the same cluster. Doing so, enabled the proposed algorithm to potentially find multiple global optima in each cluster. The performance of the proposed algorithm was evaluated by its application to the multimodal optimization of benchmark PFSSP. The results obtained were also compared to the results obtained when other niching techniques such as clearing method, sharing fitness, and a hybrid of the proposed approach and sharing fitness were used. The results of the case studies showed that the proposed algorithm was able to consistently converge to better optimal solutions than the other three algorithms.

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.

Design and Implementation of Spurs Detection System Based on OpenCV

2011 ◽  
Vol 345 ◽  
pp. 217-222
Author(s):  
Peng He ◽  
Lian Peng Wang ◽  
Na Wang ◽  
Gang Xu
Keyword(s):  
Computed Tomography ◽  
Embedded System ◽  
Detection System ◽  
Experimental Results ◽  
Design And Implementation ◽  
Function Expansion ◽  
The Embedded System ◽  
Improved Function ◽  
Small Bone ◽  
Improved Algorithm

In order to better solve the problem of detection of small bone spurs with convenient and accurate way, a portable spur detection system is designed. This system, in view of spur reproducibility characteristic, is characterized by the application for a kind of the improved algorithm based on the OpenCV. And it was successfully transplanted into the embedded system. The experimental results indicated that this system might precisely examine the small spur with difficulty discovery by naked eyes used fully by two images of computed tomography which done in different periods. The spur detection system needs to be further improved function to realize more applications. In fact, function expansion based on the system is easy to realize.

scholarly journals A New Fruit Fly Optimization Algorithm Based on Differential Evolution

2015 ◽  
Vol 3 (4) ◽  
pp. 365-373 ◽  
Author(s):  
Dabin Zhang ◽  
Jia Ye ◽  
Zhigang Zhou ◽  
Yuqi Luan
Keyword(s):  
Differential Evolution ◽  
Optimization Algorithm ◽  
Fruit Fly ◽  
Local Extremum ◽  
Experimental Results ◽  
Fruit Fly Optimization Algorithm ◽  
A Algorithm ◽  
Fruit Fly Optimization ◽  
Searching Ability ◽  
Selection Of

Abstract In order to overcome the problem of low convergence precision and easily relapsing into local extremum in fruit fly optimization algorithm (FOA), this paper adds the idea of differential evolution to fruit fly optimization algorithm so as to optimizing and a algorithm of fruit fly optimization based on differential evolution is proposed (FOADE). Adding the operating of mutation, crossover and selection of differential evolution to FOA after each iteration, which can jump out local extremum and continue to optimize. Compared to FOA, the experimental results show that FOADE has the advantages of better global searching ability, faster convergence and more precise convergence.

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