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Small Evolution Antenna Design Method Based on Dynamic Hill Climbing Algorithm and Orthogonal Experiment

Hui Shi, Junjie Li, Zhiming Xie
2019 Journal of Physics, Conference Series  
The antenna simulation results demonstrate the effectiveness and feasibility of using dynamic evolutionary algorithms for antenna design.  ...  Aiming at the complex high-dimensional and dynamic problems of aerial antenna modeling, a dynamic hillclimbing algorithm based on orthogonal design is designed and implemented to simulate and optimize  ...  optimization problem, and applies a dynamic constrained multi-objective evolutionary algorithm to solve the transformed antenna design problem.  ... 
doi:10.1088/1742-6596/1395/1/012009 fatcat:zdfx7ympyzbyxixo7lr5wwdihm

An orthogonal multi-objective evolutionary algorithm with lower-dimensional crossover

Song Gao, Sanyou, Bo Xiao, Lei Zhang, Yulong Shi, Xin Tian, Yang Yang, Haoqiu Long, Xianqiang Yang, Danping Yu, Zu Yan
2009 2009 IEEE Congress on Evolutionary Computation  
This paper proposes an multi-objective evolutionary algorithm. The algorithm is based on OMOEA-II[2]. A new linear breeding operator with lower-dimensional crossover and copy operation is used.  ...  For three problems, the obtained solutions are very close to the true Pareo Front, and for one problem, the obtained solutions distribute on part of the true Pareo Front.  ...  An Orthogonal Multiobjective Evolutionary Algorithm for Multi-objective Optimization Problems with Constraints. Evolutionary Computation, 12(1), pp77-98. [17] Montgomery, D.  ... 
doi:10.1109/cec.2009.4983180 dblp:conf/cec/GaoZXZSTYLYYY09 fatcat:chcj25kwxvcqtbsxw7kagqnz7u

Constrained multi-objective antenna design optimization using surrogates

Prashant Singh, Marco Rossi, Ivo Couckuyt, Dirk Deschrijver, Hendrik Rogier, Tom Dhaene
2017 International journal of numerical modelling  
The results are compared with well-established multi-objective optimization evolutionary algorithms.  ...  A novel surrogate-based constrained multi-objective optimization algorithm for simulation-driven optimization is proposed.  ...  The ECMO algorithm [16] extends the EMO algorithm with the ability to handle computationally expensive constrained multi-objective optimization problems.  ... 
doi:10.1002/jnm.2248 fatcat:ltm5u4dxpncltm2teppbqeogmm

A Novel Hybrid Evolutionary Algorithm for Solving Multi-Objective Optimization Problems [chapter]

Huantong Geng, Haifeng Zhu, Rui Xing, Tingting Wu
2012 Lecture Notes in Computer Science  
This paper applies an evolutionary optimization scheme , inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategies , to find approximate solutions for multiobjective  ...  optimal control problems (MOCPs) .  ...  MULTIOBJECTIVE OPTIMAL CONTROL PROBLEM Mathematically , a general multi-objective optimal control problem contains a number of objectives to be minimized and (optional) constraints to be satisfied .  ... 
doi:10.1007/978-3-642-31588-6_17 fatcat:kaqc473rkff4xhfabvsnirpygm

Optimization of grinding efficiency considering surface integrity of bearing raceway

Zhou Chang, Qian Jia
2019 SN Applied Sciences  
The genetic algorithm NSGA-II is applied to the multi-objective optimization of grinding time and material removal rate, and the Pareto set is solved.  ...  In order to improve the grinding efficiency of bearing raceways, a multi-objective optimization method that considers the surface integrity constraints of the bearing raceway is proposed.  ...  Generally, two kinds of algorithms, namely evolutionary algorithms and swarm intelligence algorithms, are used to solve multi-objective optimization problems [3] .  ... 
doi:10.1007/s42452-019-0697-8 fatcat:ch7n5u6f5bb5pheg5wsecqurzi

Multi-Objective Evolutionary Optimizations of a Space-Based Reconfigurable Sensor Network under Hard Constraints

Erfu Yang, Ahmet T. Erdogan, Tughrul Arslan, Nick Barton
2007 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security (BLISS 2007)  
This paper presents the optimizations of a space-based reconfigurable sensor network under hard constraints by employing an efficient multi-objective evolutionary algorithm (MOEA).  ...  Second, the statement of multi-objective optimization problems is mathematically formulated under multiple constraints.  ...  Optimization Algorithms To solve the aforementioned optimization problems under multi-objectives and constraints, efficient multiobjective optimization (MOO) algorithm is needed.  ... 
doi:10.1109/bliss.2007.20 dblp:conf/bliss/YangEAB07 fatcat:aogas7lzevdq5kwdjntocdgula

Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints

Erfu Yang, Ahmet T. Erdogan, Tughrul Arslan, Nick H. Barton
2009 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
This paper presents the optimizations of a space-based reconfigurable sensor network under hard constraints by employing an efficient multi-objective evolutionary algorithm (MOEA).  ...  Second, the statement of multi-objective optimization problems is mathematically formulated under multiple constraints.  ...  Optimization Algorithms To solve the aforementioned optimization problems under multi-objectives and constraints, efficient multiobjective optimization (MOO) algorithm is needed.  ... 
doi:10.1007/s00500-009-0406-4 fatcat:fnvfteir2ff57ja5ogejtvckam

Hybrid multi-objective shape design optimization using Taguchi's method and genetic algorithm

Ali R. Yıldız, Nursel Öztürk, Necmettin Kaya, Ferruh Öztürk
2006 Structural And Multidisciplinary Optimization  
An improved genetic algorithm is introduced to solve multi-objective shape design optimization problems.  ...  Finally, the shape optimization of a vehicle component is presented to illustrate how the present approach can be applied for solving multi-objective shape design optimization problems.  ...  The authors also thank Tushar Goel (Structural and Multi-disciplinary Optimization Group, University of Florida) for providing data and graphics for the test problem.  ... 
doi:10.1007/s00158-006-0079-x fatcat:5kha6jinevah3fqoqfi4qjgzdm

A new design optimization framework based on immune algorithm and Taguchi's method

Ali Rıza Yıldız
2009 Computers in industry (Print)  
A B S T R A C T This paper describes an innovative optimization approach that offers significant improvements in performance over existing methods to solve shape optimization problems.  ...  Finally, it is applied to the shape design optimization of a vehicle component to illustrate how the present approach can be applied for solving shape design optimization problems.  ...  The test problem is a minimization problem for a single objective function with two variables and two inequality constraints.  ... 
doi:10.1016/j.compind.2009.05.016 fatcat:rxo5okeenfae7omunaazp5tj6m

Initialization of a multi-objective evolutionary algorithms knowledge acquisition system for renewable energy power plants

Burak Omer Saracoglu, Miguel De Simón Martín
2018 Journal of Applied Research on Industrial Engineering  
The proposed MOPs need to be solved with one or more multi-objective algorithm, such as Multi-Objective Evolutionary Algorithms (MOEAs).  ...  The main contribution of this research is the initialization of a proposed multi-objective evolutionary algorithm knowledge acquisition system for renewable energy power plants (MOEAs-KAS-F-REPPs) (research  ...  , the Multi-objective Struggle GA (MOSGA), the Orthogonal Multi-objective Evolutionary Algorithm (OMOEA), the General Multi-objective Evolutionary Algorithm (GENMOP); the Efficient Global Optimization  ... 
doi:10.22105/jarie.2018.144919.1052 doaj:b2746e5d791149abbcd6f09baf85d8c4 fatcat:ktqc6lns35e5picnjgnrhd3x7m

A filter banks design using a multiobjecive genetic algorithm for an image coding scheme

A. Boukhobza, A. Bounoua, A. Taleb Ahmed, N. Taleb
2009 2009 16th IEEE International Conference on Image Processing (ICIP)  
We formulate the optimization problem as multi-objective and we use the Non-dominated Sorting Genetic Algorithm approach (NSGAII) to solve this problem by searching solutions that achieve the best compromise  ...  MOTS-CLÉS : filter banks design, image coding, multi-objective optimization, genetic algorithms.  ...  The problem was formulated as multi-objective and solved using the NSGAII algorithm.  ... 
doi:10.1109/icip.2009.5413533 dblp:conf/icip/BoukhobzaBTT09 fatcat:p2vpnvuxxbg3bmgbimbcxhlbva

Robust Tolerance Design in Structural Dynamics [chapter]

Chaoping Zang, Jun Yang, M. I. Friswell
2013 Topics in Model Validation and Uncertainty Quantification, Volume 5  
responses of interest; 3) identify factors to be adjusted and transform the problem into a multi-objective optimization.  ...  A systematic tolerance design strategy is required to control this kind of variation, and an approach for tolerance design based on robust design theory is proposed in this paper with a focus on the optimization  ...  Many attempts have been made to develop efficient evolutionary multi-objective algorithms.  ... 
doi:10.1007/978-1-4614-6564-5_16 fatcat:hk2gut4myvhltkjgxajuchov5y

An Improved multi-objective genetic algorithm based on orthogonal design and adaptive clustering pruning strategy [article]

Xinwu Yang, Guizeng You, Chong Zhao, Mengfei Dou, Xinian Guo
2019 arXiv   pre-print
As a classic multi-objective genetic algorithm, NSGA-II is widely used in multi-objective optimization fields.  ...  Two important characteristics of multi-objective evolutionary algorithms are distribution and convergency.  ...  Multi-Objective Evolutionary Algorithms (MOEAs) are very suitable for solving such problems and have become one of the mainstream algorithms for solving multi-objective optimization problems [1] .  ... 
arXiv:1901.00577v1 fatcat:n4kbjsfujrdpllxhb6csv6al74

Hierarchical Approach to Evolutionary Multi-Objective Optimization [chapter]

Eryk Ciepiela, Joanna Kocot, Leszek Siwik, Rafał Dreżewski
2008 Lecture Notes in Computer Science  
In this paper a new "hierarchical" evolutionary approach to solving multi-objective optimization problems is introduced.  ...  The results of experiments with standard multi-objective test problems, which were aimed at comparing "hierarchical" and "classical" versions of multiobjective evolutionary algorithms, show that the proposed  ...  Therefore, the orthogonal concerns such as: search region constraints along with genetic representation, individuals rating, and applied evolutionary algorithm are independent.  ... 
doi:10.1007/978-3-540-69389-5_82 fatcat:lzvache2ubg2dl23xlthslj4zm

Differential Evolution based Multiobjective Optimization-A Review

Deepa Sreedhar, Binu Rajan M .R
2013 International Journal of Computer Applications  
Multiobjective differential evolution(MDE) is a powerful, stochastic multi objective optimization(MOO) algorithm based on Differential Evolution(DE) that aims to optimize a problem that involves multiple  ...  This paper presents a review of some multi objective (back propagation) differential evolution algorithms. General Terms Algorithms.  ...  The solutions of the two test problem, provided by PDE algorithm, are compared with 12 other multi objective evolutionary algorithms (MEAs). Out of 12 algorithms no algorithm produces optimal result.  ... 
doi:10.5120/10541-5019 fatcat:cporrht2svc23cs45sb6hqssly
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