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A memetic algorithm using local search chaining for black-box optimization benchmarking 2009 for noisy functions

Daniel Molina, Manuel Lozano, Francisco Herrera
2009 Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09  
Experiments are carried out on the noise free Black-Box Optimization Benchmarking BBOB'2009 test suite.  ...  In this work, we show a memetic algorithm that applies CMA-ES to refine the solutions, assigning to each individual a local search intensity that depends on its features, by chaining different local search  ...  In Section 2, we describe in detail the presented algorithm. In Section 3, we present the experimental section, using the Black-Box Optimization Benchmarking for Noiseless Function (BBOB'2009).  ... 
doi:10.1145/1570256.1570329 dblp:conf/gecco/MolinaLH09a fatcat:6o533aown5ditmtbki4eafiy4i

Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking [article]

Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong, Baptiste Roziere, Jeremy Rapin, Olivier Teytaud, Antoine Moreau, Carola Doerr
2021 arXiv   pre-print
Existing studies in black-box optimization for machine learning suffer from low generalizability, caused by a typically selective choice of problem instances used for training and testing different optimization  ...  We demonstrate the advantages of such a broad collection by deriving from it Automated Black Box Optimizer (ABBO), a general-purpose algorithm selection wizard.  ...  The wide literature in algorithm selection (Rice, 1976; Smith-Miles, 2009; Kotthoff, 2014; Bischl et al., 2016; was applied to continuous black-box optimization and in a public platform in (Liu et al  ... 
arXiv:2010.04542v3 fatcat:fdpq6w66pzbrxipzb4fxd54zza

Global optimization advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO

Fani Boukouvala, Ruth Misener, Christodoulos A. Floudas
2016 European Journal of Operational Research  
Finally, an inclusive and complete test suite is provided for both MINLP and CDFO algorithms, which is useful for future benchmarking.  ...  This work provides a comprehensive and detailed literature review in terms of significant theoretical contributions, algorithmic developments, software implementations and applications for both MINLP and  ...  On the other hand, local pattern search methods are typically developed for faster grey/black-box models, which may be noisy or non-smooth.  ... 
doi:10.1016/j.ejor.2015.12.018 fatcat:jwe7b7ivrzhrjbttdl74eff2pe

Welcome message from the General Chairs

Giovanni Giambene, Boon Sain Yeo
2009 2009 International Workshop on Satellite and Space Communications  
All accepted papers will be included in the Proceeding of Adaptation, Learning and Optimization Series published by Springer-Verlag.  ...  Based on these rigorous reviews, IES 2014 accepted 106 papers for inclusion in the conference program, which represents an acceptance rate of 69%.  ...  Third, a black box diagram is applied to understand and consider the functions of a product during assembly and disassembly operations.  ... 
doi:10.1109/iwssc.2009.5286448 fatcat:wcu4uzasizhzjmdkzyekynnqwi

Population-based heuristic algorithms for continuous and mixed discrete-continuous optimization problems

Tianjun Liao
2015 4OR  
This framework synthesizes algorithmic components of two ACO algorithms that have been proposed in the literature and an incremental ACO algorithm with local search for continuous optimization, which we  ...  We also propose iCMAES-ILS, a hybrid algorithm that loosely couples IPOP-CMA-ES, a CMA-ES variant that uses a restart schema coupled with an increasing population iii v me to apply for a fellowship from  ...  CMA-ES can be used as a stand-alone algorithm but it is often used as a local optimizer in other metaheuristics [Ghosh et al., 2012 , Molina et al., 2010a , Müller et al., 2009 .  ... 
doi:10.1007/s10288-015-0285-8 fatcat:fbdeu2lx4ngghdyqenamhfckry

Shape-constrained Symbolic Regression – Improving Extrapolation with Prior Knowledge [article]

Gabriel Kronberger and Fabricio Olivetti de França and Bogdan Burlacu and Christian Haider and Michael Kommenda
2021 arXiv   pre-print
In both algorithms we use interval arithmetic to approximate bounds for models and their partial derivatives.  ...  The approach is called shape-constrained symbolic regression and allows us to enforce e.g. monotonicity of the function over selected inputs.  ...  The authors gratefully acknowledge support by the Christian Doppler Research Association and the Federal Ministry of Digital and Economic Affairs within the Josef Ressel Centre for Symbolic Regression.  ... 
arXiv:2103.15624v1 fatcat:m5ietqu7rbb47ivy4lxae323qu

Shape-constrained Symbolic Regression – Improving Extrapolation with Prior Knowledge

G. Kronberger, F. O. de Franca, B. Burlacu, C. Haider, M. Kommenda
2021 Evolutionary Computation  
In both algorithms we use interval arithmetic to approximate bounds for models and their partial derivatives.  ...  The approach is called shape-constrained symbolic regression and allows us to enforce e.g. monotonicity of the function over selected inputs.  ...  And some of the experiments (ITEA) made use of the Intel®AI DevCloud, which Intel®provided free access.  ... 
doi:10.1162/evco_a_00294 pmid:34623432 fatcat:gwyid3r3mbesxds5wmwy3hh4fm

A parallel hybrid optimization algorithm for fitting interatomic potentials

C. Voglis, P.E. Hadjidoukas, D.G. Papageorgiou, I.E. Lagaris
2013 Applied Soft Computing  
In addition, its serial implementation performs well and therefore can also be used as a general purpose optimization algorithm.  ...  We use the OpenMP tasking model to express the inherent parallelism of the algorithm on shared-memory systems and a runtime library which implements the execution environment for adaptive task-based parallelism  ...  Serial experiments In order to establish the efficiency of the chosen hybrid scheme, we have tested our serial implementation against the Black-Box Optimization Benchmarking (BBOB) 2009 test set [35]  ... 
doi:10.1016/j.asoc.2013.08.007 fatcat:tu5ijvkr2rai7k2gvy63o7xgve

Knowledge management overview of feature selection problem in high-dimensional financial data: cooperative co-evolution and MapReduce perspectives

A N M Bazlur Rashid, Tonmoy Choudhury
2019 Problems and Perspectives in Management  
Further, MapReduce, a programming model, offers a ready-to-use distributed, scalable, and fault-tolerant infrastructure for parallelizing the developed algorithm.  ...  Cooperative co-evolution, a meta-heuristic algorithm and a divide-and-conquer approach, decomposes high-dimensional problems into smaller sub-problems.  ...  A correlation-based memetic algorithm (MA) (GA plus a local search) FS tech- nique uses the symmetrical uncertainty for large- scale gene expression datasets (Kannan & Ramaraj, 2010).  ... 
doi:10.21511/ppm.17(4).2019.28 fatcat:76yr472o6rf7vm3torvgnxfcnm

A survey on optical character recognition for Bangla and Devanagari scripts

SOUMEN BAG, GAURAV HARIT
2013 Sadhana (Bangalore)  
A lot of work has been also reported on OCR efforts for various Indian scripts, like Devanagari, Bangla, Oriya, Tamil, Telugu, Malayalam, Kannada, Gurmukhi, Gujarati, etc.  ...  Future directions of research in OCR for Indian scripts have been also given.  ...  (vi) Neuromemetic model (Banashree & Vasanta 2007) : Memetic algorithms offer proficient search methods for complicated spaces to find good local optima.  ... 
doi:10.1007/s12046-013-0121-9 fatcat:4fna65koxfhw7hwehsrjhe34ma

Recent Advances in Selection Hyper-heuristics

John H. Drake, Ahmed Kheiri, Ender Özcan, Edmund K. Burke
2019 European Journal of Operational Research  
Hyper-heuristics have emerged as a way to raise the level of generality of search techniques for computational search problems.  ...  This is in contrast to many approaches, which represent customised methods for a single problem domain or a narrow class of problem instances.  ...  Real-valued black-box benchmark function optimisation Real parameter function optimisation has been an area of interest for swarm and evolutionary computation researchers for decades, and still maintains  ... 
doi:10.1016/j.ejor.2019.07.073 fatcat:ojfs237tynhxbgtyiho6dagapi

A Review of the Modification Strategies of the Nature Inspired Algorithms for Feature Selection Problem

Ruba Abu Abu Khurma, Ibrahim Aljarah, Ahmad Sharieh, Mohamed Abd Abd Elaziz, Robertas Damaševičius, Tomas Krilavičius
2022 Mathematics  
This survey is an effort to provide a research repository and a useful reference for researchers to guide them when planning to develop new Nature-inspired Algorithms tailored to solve Feature Selection  ...  We identified and performed a thorough literature review in three main streams of research lines: Feature selection problem, optimization algorithms, particularly, meta-heuristic algorithms, and modifications  ...  The bacterial evolutionary algorithm and PSO algorithm, both with a plain and a memetic variant complemented with gradient-based local search and fuzzy logic numbers were used in [93] for solving various  ... 
doi:10.3390/math10030464 fatcat:sjg667gilzfktokxxjwdg52jbm

Hybrid Evolutionary Computation for Continuous Optimization [article]

Hassan A. Bashir, Richard S. Neville
2013 arXiv   pre-print
the SQP local search algorithm.  ...  Preliminary results justify that an adept hybridization of evolutionary algorithms with a suitable local search method, could yield a robust and efficient means of solving wide range of global optimization  ...  EC algorithm (for global searching) and an interior point method (IPM) based SQP algorithm (for local searching) to address large scale global optimization problems.  ... 
arXiv:1303.3469v1 fatcat:adao7rqvm5hs5ir5u2x3eyz4mi

A Survey on fish classification Techniques

Mutasem K. Alsmadi, Ibrahim Almarashdeh
2020 Journal of King Saud University: Computer and Information Sciences  
It has been applied in a countless number of domains including target marketing.  ...  This survey also reviewed the use of Databases such as Fish4-Knowledge (F4K), knowledge database, and Global Information System (GIS) on Fishes and other FC databases.  ...  A Hybrid Memetic Algorithm (Genetic Algorithm and Great Deluge Local Search) together with Back-Propagation Classifier (HGAGD-BPC) and Back-Propagation Classifier (BPC) is used also for FC (Alsmadi et  ... 
doi:10.1016/j.jksuci.2020.07.005 fatcat:wedfhm2efzddboottjilvds7iy

A survey of Bayesian Network structure learning [article]

Neville K. Kitson, Anthony C. Constantinou, Zhigao Guo, Yang Liu, Kiattikun Chobtham
2021 arXiv   pre-print
This paper provides a comprehensive review of combinatoric algorithms proposed for learning BN structure from data, describing 61 algorithms including prototypical, well-established and state-of-the-art  ...  Bayesian Networks (BNs) have become increasingly popular over the last few decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology, epidemiology, economics and the social  ...  Each box in this ordering lattice represents one of the possible sub-DAGs in a small network with nodes {1, 2, 3, 4}. The optimal DAG is determined by a depth first search of this lattice.  ... 
arXiv:2109.11415v1 fatcat:tj4ceig7rvbb3k4bqffvdvvwye
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