286 Hits in 6.9 sec

Structural bias in population-based algorithms

Anna V. Kononova, David W. Corne, Philippe De Wilde, Vsevolod Shneer, Fabio Caraffini
2015 Information Sciences  
For such algorithms to be successful, at least three properties are required: (i) an effective informed sampling strategy, that guides the generation of new candidates on the basis of the fitnesses and  ...  This reveals how structural bias can arise and manifest as non-uniform clustering of the population over time.  ...  We apply these three tests to each of two kinds of long sequences, one coming from a true random generator and another from a pseudorandom generator used to produce results in Section 3.  ... 
doi:10.1016/j.ins.2014.11.035 fatcat:niiviam3rjaw3egivmhwe42l4q

Structural bias in population-based algorithms [article]

Anna V. Kononova and David W. Corne and Philippe De Wilde and Vsevolod Shneer and Fabio Caraffini
2014 arXiv   pre-print
For such algorithms to be successful, at least three properties are required: an effective informed sampling strategy, that guides generation of new candidates on the basis of fitnesses and locations of  ...  is calculated via a fitness function specific to the problem.  ...  We apply these three tests to each of two kinds of long sequences, one coming from a true random generator and another from a pseudorandom generator used to produce results in Section 3.  ... 
arXiv:1408.5350v1 fatcat:36whh5ltenfmxkzz4wgk6aavpe

Genetic Optimization Using Derivatives

Jasjeet S. Sekhon, Walter R. Mebane
1998 Political Analysis  
We also use a system of four simultaneous nonlinear equations that has many parameters and multiple local optima to compare the performance of GENOUD to that of the Gauss-Newton algorithm in SAS's PROC  ...  We describe a new computer program that combines evolutionary algorithm methods with a derivative-based, quasi-Newton method to solve difficult unconstrained optimization problems.  ...  Whole non-uniform mutation does non-uniform mutation for all the parameters in the vector.  ... 
doi:10.1093/pan/7.1.187 fatcat:wev6hfycfjagnkl3oc6ywypfp4

Study on the Effects of Pseudorandom Generation Quality on the Performance of Differential Evolution [chapter]

Ville Tirronen, Sami Äyrämö, Matthieu Weber
2011 Lecture Notes in Computer Science  
Experiences in the field of Monte Carlo methods indicate that the quality of a random number generator is exceedingly significant for obtaining good results.  ...  This result has not been demonstrated in the field of evolutionary optimization, and many practitioners of the field assume that the choice of the generator is superfluous and fail to document this aspect  ...  Considering the number of pseudorandom numbers generated in a single run, or worse, a batch of runs by DE, this is quite significant amount.  ... 
doi:10.1007/978-3-642-20282-7_37 fatcat:lk6odagvkzg4bmy5cpi2ubdzte

Multi-GPU Island-Based Genetic Algorithm

Namrata Mahakalkar, A. R Mahajan
2020 International journal of recent advances in engineering & technology  
The proposed implementation employs an island-based genetic algorithm where every GPU evolves a single island.  ...  This paper introduces a novel implementation of the genetic algorithm exploiting a multi-GPU cluster.  ...  A fitness-based or uniform selection is carried out to select parent chromosomes to undergo crossover and produce offsprings, In this paper, we present a generic framework for Genetic Algorithms accelerated  ... 
doi:10.46564/ijraet.2020.v08i02.06 fatcat:cfwgnq2ghfbzpmcsuur3x2qazi

Transit network design and scheduling using genetic algorithm – a review

Amita Johar, S. S. Jain, P. K. Garg
2016 An International Journal of Optimization and Control: Theories & Applications  
To overcome these problems, most of the researchers have applied genetic algorithm for designing and scheduling of transit network.  ...  After the review of various studies involved in design and scheduling of transit network using genetic algorithm, it was concluded that genetic algorithm is an efficient optimization technique.  ...  Acknowledgments The financial support in the form of MHRD  ... 
doi:10.11121/ijocta.01.2016.00258 fatcat:rmfliaii3vhi5p2zkmrlpy7jve

Genetic Algorithm by using MATLAB Program

Mashal Alenazi
2015 IJARCCE  
In this paper, an attractive approach for teaching genetic algorithm (GA) is presented.  ...  A detailed illustrative examples is presented to demonstrate that how to solve Traveling Salesman Problem (TSP) and Drawing the largest possible circle in a space of stars without enclosing any of them  ...  ACKNOWLEDGMENT I would like to knowledge Prof. Prabir Patra Head of Department of Biomedical Engineering, and Prof.  ... 
doi:10.17148/ijarcce.2015.41170 fatcat:wjokk6pgejaz3brlyucgvhafiu

Random and Deterministic Digit Permutations of the Halton Sequence [chapter]

Giray Ökten, Manan Shah, Yevgeny Goncharov
2012 Monte Carlo and Quasi-Monte Carlo Methods 2010  
We use a recent genetic algorithm, test problems from numerical integration and computational ...nance, and a recent randomized quasi-Monte Carlo method, to compare generalized Halton sequences with randomly  ...  Some of the permutations in the literature are designed to minimize some measure of discrepancy, and some are obtained heuristically.  ...  The algorithm we use to compute approximations for the star-discrepancy is a novel approach that uses genetic algorithms (see Shah [15] ).  ... 
doi:10.1007/978-3-642-27440-4_35 fatcat:s5ina6ftrfbyjjghlzpfhhquvu

Application of Genetic Algorithm to Estimate the Large Angular Scale Features of Cosmic Microwave Background [article]

Parth Nayak, Rajib Saha
2021 arXiv   pre-print
Genetic Algorithm (GA) – motivated by the natural evolutionary process – is a robust method to estimate the optimal solutions of problems involving one or more objective functions.  ...  To avoid getting trapped into a local minimum, we implement the GA with generous diversity in the populations.  ...  DATA AVAILABILITY The data pertaining to this article will be shared on reasonable request to the corresponding author.  ... 
arXiv:2102.06569v1 fatcat:evd4iex5frbyrclmkrakhce25m

Current Issues in Sampling-Based Motion Planning [chapter]

Stephen R. Lindemann, Steven M. LaValle
2005 Springer Tracts in Advanced Robotics  
The simplicity of this approach, along with increases in computation power and the development of efficient collision detection algorithms, has resulted in the introduction of a number of powerful motion  ...  We then discuss a variety of important issues for sampling-based motion planning, including uniform and regular sampling, topological issues, and search philosophies.  ...  Acknowledgement We thank Pekka Isto for bringing Glavina's work to our attention. We are grateful for the funding provided in part by NSF awards 9875304, 0118146, and 0208891.  ... 
doi:10.1007/11008941_5 fatcat:kzhor5pvyjd5vf45pn47apsebm

An Overview of Evolutionary Algorithms toward Spacecraft Attitude Control [chapter]

Matthew A. Cooper, Brendon Smeresky
2020 Advances in Spacecraft Attitude Control  
In summary, the genetic algorithm and its variants can be used for a large parameter space but is more efficient in global optimization using a smaller chromosome size such that the number of parameters  ...  Evolutionary algorithms can be used to solve interesting problems for aeronautical and astronautical applications, and it is a must to review the fundamentals of the most common evolutionary algorithms  ...  However, if a problem can be defined in an approachable way, evolutionary algorithms can provide a simpler and quicker way to find a viable solution.  ... 
doi:10.5772/intechopen.89637 fatcat:2sklygbmtfespf3f3m5aj7tvey

Cellular Automata in Cryptographic Random Generators [article]

Jason Spencer
2013 arXiv   pre-print
In particular, we focus on cyclic linear and non-linear au- tomata in some of the common configurations to be found in the literature.  ...  In this effort, we focus on pseudorandom bit generation and noninvertibility, the behavioral heart of cryptography.  ...  Acknowledgements Thanks to all my friends and family for excusing the many absences over the years.  ... 
arXiv:1306.3546v1 fatcat:v6xyjyjscvfgdp2hiwy7t4c6iq

Optimization Strategies in Design Space Exploration [chapter]

Jacopo Panerati, Donatella Sciuto, Giovanni Beltrame
2016 Handbook of Hardware/Software Codesign  
Results show how the metrics can be related to the properties of a target design space (size, number of variables, and variable ranges) with a focus on accuracy, precision, and performance.  ...  This chapter presents guidelines to choose an appropriate exploration algorithm, based on the properties of the design space under consideration.  ...  Non-dominated Sorting Genetic Algorithm (NSGA) NSGA [34] is a very successful application of the genetic approach to the problem of multi-objective optimization.  ... 
doi:10.1007/978-94-017-7358-4_7-1 fatcat:cnzulf533jcjpitbyl3xbgxx6e

Evolutionary improvement of search queries and its parameters

Pavel Kromer, Vaclav Snasel, Jan Platos, Ajith Abraham
2010 2010 10th International Conference on Hybrid Intelligent Systems  
In this paper, we investigate evolutionary algorithms (in particular genetic programming) as a tool for the optimization of user queries and seek for its good settings.  ...  In the complex environment of the World Wide Web and other large data collections, it is often not easy for the users to express their information needs in an optimal way.  ...  ACKNOWLEDGEMENT This work was supported by the Ministry of Industry and Trade of the Czech Republic, under the grant no. FR-TI1/420.  ... 
doi:10.1109/his.2010.5600018 dblp:conf/his/KromerSPA10 fatcat:7zc6spkxmjdkdheuxmvw6otwwa

Heuristic Search of (Semi-)Bent Functions based on Cellular Automata [article]

Luca Mariot, Martina Saletta, Alberto Leporati, Luca Manzoni
2021 arXiv   pre-print
An interesting thread in the research of Boolean functions for cryptography and coding theory is the study of secondary constructions: given a known function with a good cryptographic profile, the aim  ...  In this work, we continue the investigation of a secondary construction based on cellular automata, focusing on the classes of bent and semi-bent functions.  ...  Sipper and Tommasini [39] were the first to propose the use of non-uniform CA to generate pseudorandom sequences, i.e. CA where each cell may use a different local rule to update its state.  ... 
arXiv:2111.13248v1 fatcat:5geqlgjhwjd2deaopvi6gfifwa
« Previous Showing results 1 — 15 out of 286 results