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Optimizing Hybrid Basis Function Types in Functional Network Design via Cultural Algorithm

Peigang Guo, Yongquan Zhou
2014 Mathematical and Computational Applications  
This method can get the hybrid basis function and its parameters with optimal searching achieving the learning between functional network structure and the functional parameters, and each model of the  ...  In this paper, a novel functional network designing method based on cultural algorithm is proposed.  ...  Through the hybrid basis function is introduced, and the use of traditional genetic algorithm of binary coding method to optimize learning hybrid basis function, application of  R squared criterion )  ... 
doi:10.3390/mca19010050 fatcat:yng3tzgiwrc2dbzrusrutbqkei


Stefan Andreea-Mirabela
2020 Annals of the University of Craiova: Economic Sciences Series  
The purpose of thispaperistopresentthehybridizationprocessandhybridalgorithms. More over, anothergoalistorevealsomepossibilities of metaheuristics, such as hybridization of algorithms.  ...  The real problem for investorsistotaketherightdecisionand, for that, theyhavetobuildforecastmodels, tomakesomeassumptions for defaultvariables, which are difficulttounderstand.  ...  So, for comprehensive combinatorial problems, genetic algorithms are being harmed by the complexity of the calculations.  ... 
doaj:1da1c0b6baae445d850036204b262ba4 fatcat:ezkjfryay5g7bdge46tb6m2qyy

A Review On Memetic Algorithms and Its Developments

2022 Electrical and Automation Engineering  
Magic the study of information and culture in terms of its analogy with Darwinian evolution. Spiritualists describe this as an approach to evolutionary models of cultural interactions.  ...  My metric algorithm in computer science and functional research is an extension of traditional genetics. Algorithm this will provide a good enough solution to an optimization problem.  ...  Operators Hybrid Genetic Algorithms or Genetic Local Church, MS Hybrid Evolution Algorithms The basic built-in file is provided with a well-developed algorithm (NBLEA). For SMD1-SMD12.  ... 
doi:10.46632/eae/1/1/2 fatcat:t7yc5sew7vbvlmeywdihngnzui

The Relationship between Metaheuristics Stopping Criteria and Performances

Mohamed-Mahmoud Ould Sidi, Bénédicte Quilot-Turion, Abdeslam Kadrani, Michel Génard, Françoise Lescourret
2014 International Journal of Applied Metaheuristic Computing  
This paper addresses this issue using the Non-dominated Sorting Genetic Algorithm (NSGA-II) and the Multi-Objective Particle Swarm Optimization with Crowding Distance (MOPSO-CD) for the model-based design  ...  A major difficulty in the use of metaheuristics (i.e. evolutionary and particle swarm algorithms) to deal with multi-objective optimization problems is the choice of a convenient point at which to stop  ...  This optimization involves identifying a set of good combinations of genetic resources and cultural practices adapted to specific environments.  ... 
doi:10.4018/ijamc.2014070104 fatcat:l4vucmukfzbfrle436es3d477a

2010 Index IEEE Transactions on Evolutionary Computation Vol. 14

2010 IEEE Transactions on Evolutionary Computation  
., +, TEVC Aug. 2010 602-617 + Check author entry for coauthors Hybrid Genetic Algorithm Using a Forward Encoding Scheme for Lifetime Maximization of Wireless Sensor Networks. Hu, X.  ...  ., +, TEVC Oct. 2010 766-781 Energy conservation Hybrid Genetic Algorithm Using a Forward Encoding Scheme for Lifetime Maximization of Wireless Sensor Networks. Hu, X.  ... 
doi:10.1109/tevc.2010.2097050 fatcat:qhxnf2o62bd3xmxsfyd5fb37ym

Parallel Hybrid Metaheuristics [chapter]

Carlos Cotta, El-Ghazali Talbi, Enrique Alba
2005 Parallel Metaheuristics  
The flexibility of these techniques makes them prime candidates for tackling both new problems and variants of exiting problems. This fact, i  ...  of distribution algorithms (EDAs) [79], and others.  ...  Hybrid algorithms such as the island model for GAs [111] , belong to this class of hybrids.  ... 
doi:10.1002/0471739383.ch15 fatcat:frvcocssmbalbgx6lwnjbj3npu

A hybrid approach of support vector regression with genetic algorithm optimization for aquaculture water quality prediction

Shuangyin Liu, Haijiang Tai, Qisheng Ding, Daoliang Li, Longqin Xu, Yaoguang Wei
2013 Mathematical and computer modelling  
This study presents a hybrid approach, known as real-value genetic algorithm support vector regression (RGA-SVR), which searches for the optimal SVR parameters using real-value genetic algorithms, and  ...  then adopts the optimal parameters to construct the SVR models.  ...  This study presents a hybrid approach, known as real-value genetic algorithm support vector regression (RGA-SVR), which searches for the optimal SVR parameters using real-value genetic algorithms, and  ... 
doi:10.1016/j.mcm.2011.11.021 fatcat:eq4wfr2mqvho7jsggokiw4dqaq

Using Datamining Techniques to Help Metaheuristics: A Short Survey [chapter]

Laetitia Jourdan, Clarisse Dhaenens, El-Ghazali Talbi
2006 Lecture Notes in Computer Science  
Hybridizing metaheuristic approaches becomes a common way to improve the efficiency of optimization methods. Many hybridizations deal with the combination of several optimization methods.  ...  In this paper we are interested in another type of hybridization, where datamining approaches are combined within an optimization process.  ...  We can remark that usually the authors use classification methods (C4.5, AQ, etc) to identify the genes that induce the good quality of the individuals.  ... 
doi:10.1007/11890584_5 fatcat:4pahhlpfzrbwvjf2zwezpz3z2m

Hybrid Ant Colony Optimization Using Memetic Algorithm for Traveling Salesman Problem

Haibin Duan, Xiufen Yu
2007 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning  
This hybrid approach is also valid for other types of combinational optimization problems.  ...  Memetic algorithm is a population-based heuristic search approach which can be used to solve combinatorial optimization problem based on cultural evolution.  ...  AKNOWLEDGEMENT The authors are grateful to the anonymous referees for their valuable comments and suggestions that have led to the better presentation of this paper.  ... 
doi:10.1109/adprl.2007.368174 fatcat:w35nfikj6jh2xaqerrn7byde4e

A dual encoding-based meta-heuristic algorithm for solving a constrained hybrid flow shop scheduling problem

Antonio Costa, Fulvio Antonio Cappadonna, Sergio Fichera
2013 Computers & industrial engineering  
A mixed integer linear programming model of the problem in hand has been developed with the aim to validate the performance concerning the proposed optimization technique, based on a two-phase metaheuristics  ...  the algorithm strength in terms of both exploration and exploitation.  ...  Genetic Algorithms efficacy and efficiency for solving FSMP problems has been documented by Sivrikaya Serifoglu and Ulusoy (2004) .  ... 
doi:10.1016/j.cie.2013.01.004 fatcat:dnwmzxg3qfhwhlramvlx5k7g6m

Recent Progress on Graph Partitioning Problems Using Evolutionary Computation [article]

Hye-Jin Kim, Yong-Hyuk Kim
2018 arXiv   pre-print
The graph partitioning problem (GPP) is a representative combinatorial optimization problem which is NP-hard. Currently, various approaches to solve GPP have been introduced.  ...  In section 2, research related to the encoding of genetic algorithm (GA) is covered. In Section 3, local optimization used in the multi-level heuristic, and the hybrid method are introduced.  ...  The Fiduccia-Mattheyses algorithm [4] was used for local optimization and operators were revised to apply QEA. Hwang et al.  ... 
arXiv:1805.01623v1 fatcat:x6ww35oxpvfrpdy3m4c2znk6n4

Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey

Mohammad-H. Tayarani-N., Xin Yao, Hongming Xu
2015 IEEE Transactions on Evolutionary Computation  
parts of engines and modeling.  ...  There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling.  ...  Calibrating the parameters of the model of a diesel engine was studied in [182] , and a hybrid genetic algorithm and ant colony optimization algorithm were employed.  ... 
doi:10.1109/tevc.2014.2355174 fatcat:le2et3abrjbcbf5jxzgs2gff54

Combining simplex with niche-based evolutionary computation for job-shop scheduling

Syhlin Kuah, Joc Cing Tay
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
We propose a hybrid algorithm (called ALPINE) between Genetic Algorithm and Dantzig's Simplex method to approximate optimal solutions for the Flexible Job-Shop Problem.  ...  Performance results on benchmark problems show that ALPINE outperforms existing hybrid techniques with a new global optima found for the 10x7 Flexible Job Shop Problem.  ...  In this paper, we propose a hybrid algorithm between Genetic Algorithm and a classical optimization method -Dantzig's Simplex method, to approximate optimal solutions to the FJSP.  ... 
doi:10.1145/1143997.1144101 dblp:conf/gecco/KuahT06 fatcat:2e4bwk52ezajlhmfy66jjeknxi

Biosocial Culture Inspired Hierarchical Algorithm for MISO Block Oriented Nonlinear System Identification: Application to Ozone Modelling

A. Naitali, F. Giri, E. Elayan, M. Haloua
2008 IFAC Proceedings Volumes  
A hybrid genetic and swarming intelligence based Hierarchical Cultural Algorithm is used to adapt the structure of the bad less suited model and to estimate the parameters of its dynamics and nonlinearities  ...  A new solution to nonlinear systems identification of MISO Hammerstein and/or Wiener models is developed using tools from Evolutionary Computation based optimization.  ...  be actually as one of most powerful evolutionary solution to continuous optimization problems, an hybridizing scheme based on a collaborative association, between Genetic adaptation and Particle Swarming  ... 
doi:10.3182/20080706-5-kr-1001.01256 fatcat:c4paomxctfh47o7c6uxmbbqsgu

A Cultural Algorithm for POMDPs from Stochastic Inventory Control [chapter]

S. D. Prestwich, S. A. Tarim, R. Rossi, B. Hnich
2008 Lecture Notes in Computer Science  
We describe a cultural algorithm for POMDPs that hybridises SARSA with a noisy genetic algorithm, and inherits the latter's convergence properties.  ...  Neither SARSA nor the genetic algorithm dominates the other on these problems, but the cultural algorithm outperforms the genetic algorithm, and on highly non-Markovian instances also outperforms SARSA  ...  Cultural reinforcement learning We propose a new cultural hybrid of reinforcement learning and evolutionary computation for solving POMDPs called CUltural Reinforcement Learning (CURL).  ... 
doi:10.1007/978-3-540-88439-2_2 fatcat:mcxzqf7pgvalxedlvesy2qiivm
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