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A Hybrid Pso and Shuffled Complex evolution algorithm for Order Assignment Problem in Holonic Manufacturing System

International Conference on Manufacturing Science and Engineering (ICMSE 2009)

作者： Zhao, Fuqing Zou, Jianhua Sheng, Shangxiong Xi An Jiao Tong Univ Syst Engn Inst Xian 710049 Peoples R China Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Peoples R China

ISBN: (纸本)9780878492800

Today's market dynamics have made operation process in manufacturing system extremely complex and difficult. Enterprise need to continuous adjust its strategies on evaluating and designing their task and order assignment methods to provide products at the lowest possible cost while reducing the total lead time. The evaluation model based on Holonic Manufacturing System is presented in this paper. The model incorporates operation cost and lead time as the object. A hybrid PSO algorithm with Shuffled Complex evolution algorithm(SCE) is utilized to compute the combination optimum for Order assignment problem. Simulation result shows that the model and the algorithm are effective to the problem.

关键词： Holonic Manufacturing Systems Particle swarm optimization (PSO) Shuffled Complex evolution evolution algorithm

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A Synthesis of Four-Branch Microwave Antenna by evolution algorithm and Orthogonal Experiment

A Synthesis of Four-Branch Microwave Antenna by Evolution Al...

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5th International Symposium on Intelligence Computation and Applications

作者： Guo, Jincui Zou, Jinxin Wang, Yincheng Zhao, Xiaojuan Yu, Liangjiang China Univ Geosci Fac Mech & Elect Informat Wuhan 430074 Peoples R China

ISBN: (纸本)9783642164927

In order to meet the design requirements of a wide bandwidth, wide beam four-branch microwave antenna, evolution algorithms and orthogonal experiment are combined for the design simulation of the microwave antenna design. The evolution algorithm is able to search the large space for the optimal solution, while the orthogonal experimental design can search local space further and refine it for even better solution. The former algorithm is executed parallelly, and the NEC2 software based on method of moments is used is numerical calculation method of electromagnetic field. The four-branch antenna which is designed by combining the method of the evolution algorithm with orthogonal experiment in this paper, performs excellent on pattern. This proves that this method can satisfy the design requirements.

关键词： evolution algorithm orthogonal design method of moments satellite antenna

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An Adaptive Response Surface Method Combined with (1-λ) evolution algorithm and its Application to Optimal Design of Electromagnetic Devices

An Adaptive Response Surface Method Combined with (1-λ) Evo...

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5th IEEE Conference on Industrial Electronics and Applications

作者： Zhang, Yanli He, Houjian Koh, Chang Seop Shenyang Univ Technol Sch Elect Engn Shenyang Peoples R China

ISBN: (纸本)9781424450466

This paper presents a global optimization algorithm combining an adaptive response surface approximation of the objective function and (1+lambda) evolution algorithm. In the adaptive approximation, an optimal Latin hypercube sampling strategy based on multi-objective Pareto optimization is developed to obtain the sampling data in the design variable space, and multiquadric radial basis function is employed to construct the response surface. The proposed method is tested and applied to the optimal design of permanent magnet linear synchronous motors.

关键词： central composite design evolution algorithm Latin hybercube design Pareto-optimization response surface method

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Optimization of Suspension Design Based on evolution algorithm for a Novel E-bike

Optimization of Suspension Design Based on Evolution Algorit...

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9th World Congress on Intelligent Control and Automation (WCICA)

作者： Lin, Chih-Jer Lin, Po-Ting Yu, Shen-Kai Hu, I-Lu Natl Taipei Univ Technol Grad Inst Automat Technol Taipei Taiwan Da Yeh Univ Dept Mech & Automat Engn Changhua 51505 Taiwan

ISBN: (纸本)9781612847009

The objective of this study is to develop a novel design of electric bike. The authors used some engineering approach packages in this study to analyze kinetic and dynamics of the system. The newly developed suspension design of the E-bike will also be incorporated using ADAMS and BikeSim simulation into the design consideration of suspension. To improve the ride comfort and driving safety of the E-bike, an optimization problem is formulated based on the comfort and safety cost function. To obtain the optimal performance for the proposed suspension, evolution algorithms (EAs) are studied to obtain the optimal suspension parameters.

关键词： evolution algorithm suspension design Adams

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A Matrix Adaptation evolution Strategy Based evolution algorithm for Large-scale Many-objective Optimization 32

A Matrix Adaptation Evolution Strategy Based Evolution Algor...

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32nd Chinese Control And Decision Conference (CCDC)

作者： Yang, Ling Liu, Jianchang Li, Fei Tan, Shubin Zheng, Tianzi Liu, Yuanchao Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China Anhui Univ Technol Dept Elect & Informat Engn Maanshan 243032 Anhui Peoples R China

ISBN: (纸本)9781728158556

In recent years, multi-objective optimization problems have been received a lot of attention. However, many applications involve hundreds or thousands of decision variables, which pose a serious barrier for evolutionary algorithms. In this paper, therefore, a novel algorithm, denoted as matrix adaptation evolution strategy based evolution algorithm (MAES-EA), is proposed for large-scale multi-objective optimization. In the proposed algorithm, the decision variables are divided into convergence related variables and diversity related variables, which are optimized by different optimization strategies. To be specific, the matrix adaptation evolution strategy is introduced to reduce the amount of evaluations when optimizing the convergence related variables. In addition, the L-0.5-norm-based distance is applied to optimize diversity related variables. The performance of the proposed algorithm is compared with some state-of-the-art methods on LSMOP test instances, and results show that MAES-EA is suitable for large-scale multi-objective optimization.

关键词： MAES Large-scale multi-objective optimization decision variables evolution algorithm

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Modular Feedback Assistance Hybrid evolution algorithm Based on Cloud Environment for Job Shop Scheduling Problem Optimization 6

Modular Feedback Assistance Hybrid Evolution Algorithm Based...

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6th International Conference on Applications of Digital Information and Web Technologies (ICADIWT)

作者： Jian, Ming-Shen Jhou, Yi-Chen You, Ming-Sian Natl Formosa Univ Dept Comp Sci & Informat Engn Huwei Yunlin County Taiwan

ISBN: (纸本)9781614995036;9781614995029

This paper develops cloud based software computing as a service (SCaaS) in hybrid evolution algorithm with feedback assistance to find the optimal solution of NP-complete problems such as job shop scheduling problems. In this paper, the different steps and types of the evolution algorithm can be established via individual thread procedures and various virtual machines in cloud. During the evolution steps, methods, or procedures of the genetic algorithm, the fitness evaluation result and survival ratio of different crossover methods in the current generation can be used for the feedback assistance method. The proposed feedback assistance method can be added into the evolution procedure and dynamically emphasize the corresponding methods or procedures with better performance in optimal solution searching. All the steps or methods in genetic algorithm are created similar to the MapReduce structure. Furthermore, via using the feedback assistance, the convergence time of the optimal solution can be enhanced.

关键词： evolution algorithm Cloud Modular Feedback Hybrid

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Improved evolution algorithm that Guides the Direction of Individual Mutation for Influence Maximization in Social Networks 14th

Improved Evolution Algorithm that Guides the Direction of In...

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14th International Conference on Knowledge Science, Engineering, and Management (KSEM)

作者： Tang, Xiaoqin Liu, Xuxing Southwest Univ Coll Comp & Informat Sci Chongqing 400715 Peoples R China

ISBN: (纸本)9783030821531;9783030821524

The purpose of influence maximization in social networks is to find K nodes as the spread source to activate as many nodes as possible. To improve the efficiency and effectiveness of the classic genetic algorithm in large social networks, the diffusion evaluation function is first proposed to estimate the impact range of seed nodes. Then the individuals are initialized based on the diffusion degree centrality of the node. Adapted a crossover strategy is used to help the evolution algorithm to achieve the purpose of local search. Besides, a direction vector is designed to guide the individual's mutation. Through experiments on real social networks, the improved evolution algorithm can approximate the state-of-the-art greedy algorithm in the final result while also significantly improving time efficiency.

关键词： Influence maximization evolution algorithm Diffusion evaluation function Crossover strategy Direction vector

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evolution algorithm of parametric active contour model based on Gaussian smoothing filter

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MACHINE VISION AND APPLICATIONS 2022年第6期33卷 83-83页

作者： Tang, Kelun Zhou, Xiaojun Xihua Univ Chengdu 610039 Peoples R China

At present, the parametric active contour model is one of the most well-known and widely used image segmentation techniques in image processing and computer vision. However, its evolution computation is slow, which is a great obstacle to some applications such as real-time motion tracking. This paper not only reveals its bottleneck including the high computation cost of the inverse operation of matrix and the matrix multiplication in each iteration, but also proposes a novel scheme that transfers these time-consuming matrix operations into vector convolution operations for better performance. As shown by simulation results the proposed algorithm is always much faster than the conventional algorithm, and the velocity gain increases with the snaxels on the curve, from several times to over 2 orders of magnitude.

关键词： Gaussian smoothing filter evolution algorithm Parametric active contour model Convolution operation

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Manifold Block Optimization Method by Utilizing evolution algorithm

Manifold Block Optimization Method by Utilizing Evolution Al...

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21st Chinese Control and Decision Conference

作者： Yin, Jingben Zhao, Lei Wang, Juntao Henan Inst Sci & Technol Dept Math Xinxiang 453003 Peoples R China

ISBN: (纸本)9781424427239

In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 programs. In our designed visual basic 6.0 programs the geometric parameters of hydraulic elements are putted into special designed drawing interface procedure, so the manifold block drawing of hydraulic system can be automatically produced by our designed procedure. At finally, the numerical results by the designed procedure implies that the computational efficiency is greatly improved and the computational time of designing is largely shortened.

关键词： optimization design manifold block design evolution algorithm

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Multi-Objective Optimization Based on Adaptive evolution algorithm for Disassembly Line Network Problems 24

Multi-Objective Optimization Based on Adaptive Evolution Alg...

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24th International Conference on Advanced Communication Technology (ICACT) - Artificial Intelligence Technologies toward Cybersecurity

作者： Jian, Ming-Shen Wu, Wei-Sin Lin, Yi-Hsuan Wu, Xin-Mei Wang, Peng-Wen Natl Formosa Univ Dept CSIE Cloud Comp & Intelligent Serv Lab Huwei Taiwan

ISBN: (纸本)9791188428090

In recent years, the demand for disassembly is increasing. the variability of the feed product and the degree of damage that occurs during the disassembly process. In this research, the optimized mathematical programming models are proposed based on the transformed AND / OR graphic(TAOG) as a priority relation between jobs. To find the optimal solution, different steps and types of the evolution algorithm can be established via individual thread procedures and various virtual machines in cloud. The proposed improvement phase based on the fitness evaluation result according to different crossover methods can enhance the performance of the convergence.

关键词： Multi-Objective evolution algorithm disassembly line optimal solution

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