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A Probabilistic Memetic Framework

Quang Huy Nguyen, Yew-Soon Ong, Meng Hiot Lim
2009 IEEE Transactions on Evolutionary Computation  
involving the decision of embracing the separate actions of evolution or individual learning and analyze the probability of each process in locating the global optimum.  ...  Memetic algorithms (MAs) represent one of the recent growing areas in evolutionary algorithm (EA) research.  ...  A Probabilistic Memetic Framework for Non-Linear Optimization Optimization is the study of the mathematical properties of optimization problems and the analysis of algorithms.  ... 
doi:10.1109/tevc.2008.2009460 fatcat:d66blwyqcng5bn6msqp2gdapom

Synthesis of the -distribution as an aid to stochastic global optimization

M.M. Ali
2007 Computational Statistics & Data Analysis  
The -distribution is used as a point generation scheme in global optimization. Two population set-based global optimization algorithms are considered.  ...  The hybridization uses a probabilistic combination of the point generation by the -distribution and the point generation by DE or CRS.  ...  Drigo of the School of Statistics and Actuarial Science, University of the Witwatersrand, Johannesburg.  ... 
doi:10.1016/j.csda.2006.12.011 fatcat:fx3lvug2hngwplztrrv43qcsba

A Random Search Framework for Convergence Analysis of Distributed Beamforming With Feedback

Che Lin, Venugopal V. Veeravalli, Sean P. Meyn
2010 IEEE Transactions on Information Theory  
Furthermore, it is established that the time required for the adaptive scheme to converge in mean scales linearly with respect to the number of sensor/relay nodes.  ...  Using these properties and the systematic framework, it is shown that the adaptive distributed beamforming scheme converges both in probability and in mean.  ...  Simulated annealing is a generic probabilistic algorithm that approximates the global optimal solution of a given function in a large search space.  ... 
doi:10.1109/tit.2010.2080590 fatcat:jfjzro47grezjp3gqq2zwo2nbm

Probabilistic Electric Vehicle Charging Optimized With Genetic Algorithms and a Two-Stage Sampling Scheme

Stephan Hutterer, Michael Affenzeller
2013 International Journal of Energy Optimization and Engineering  
Using simulation-based optimization, such probabilistic and dynamic behavior can be fully integrated within the metaheuristic optimization process, yielding into a generic approach suitable for optimization  ...  Probabilistic power flow studies represent essential challenges in nowadays power system operation and research.  ...  Thus, parameterization and adaptation of a suitable optimization algorithm will be discussed, introducing a novel approach for adaptive fitness-based sampling when evaluating a solution candidate in an  ... 
doi:10.4018/ijeoe.2013070101 fatcat:4zygo2ftfvf5tj2fotj62x2j5u

A study of self-organization mechanisms in ad hoc and sensor networks

Falko Dressler
2008 Computer Communications  
The main contribution of this paper is a categorization of self-organization methodologies. Additionally, well-known methods in ad hoc networks are classified and some case studies are provided.  ...  Until now, many self-organization methods have been developed for communication networks in general and ad hoc networks in particular.  ...  The period can be adapted to the carrier sensing algorithm in order to optimize the behavior of the protocol.  ... 
doi:10.1016/j.comcom.2008.02.001 fatcat:rpwbzpmpnvdwtgxpgypaai3hgy

Page 4395 of Mathematical Reviews Vol. , Issue 95g [page]

1995 Mathematical Reviews  
Global Optim. 5 (1994), no. 2, 127-129. The Steiner tree problem deals with finding the shortest network interconnecting a given set of points in a metric space.  ...  Yet numerical experiments show that for many applied problems the global extremum point is not attained in an acceptable time. The algorithms proposed by L. F.  ... 

On path planning strategies for networked unmanned aerial vehicles

Evsen Yanmaz, Robert Kuschnig, Markus Quaritsch, Christian Bettstetter, Bernhard Rinner
2011 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)  
In this paper, we compare deterministic and probabilistic path planning strategies for an autonomous unmanned aerial vehicle (UAV) network, where the objective is to explore a given area with obstacles  ...  We present both online and offline implementations of the algorithms as alternative solutions, where applicable, and analyze the performance of the offline implementations.  ...  ACKNOWLEDGMENT This work was performed in the project Collaborative Microdrones of Lakeside Labs and was partly funded by the ERDF, the KWF, and the state of Austria under grant 20214/17095/24772.  ... 
doi:10.1109/infcomw.2011.5928811 fatcat:hpf3e4mvcvghxdaf67bbgyayje

A Random Search Framework for Convergence Analysis of Distributed Beamforming with Feedback [article]

C. Lin, V. V. Veeravalli, S. Meyn
2010 arXiv   pre-print
Furthermore, it is established that the time required for the adaptive scheme to converge in mean scales linearly with respect to the number of sensor/relay nodes.  ...  The focus of this work is on the analysis of transmit beamforming schemes with a low-rate feedback link in wireless sensor/relay networks, where nodes in the network need to implement beamforming in a  ...  Simulated annealing is a generic probabilistic algorithm that approximates the global optimal solution of a given function in a large search space.  ... 
arXiv:0806.3023v3 fatcat:yng6blhvbjhwrhao6o5ahcojne

Page 5504 of Mathematical Reviews Vol. , Issue 94i [page]

1994 Mathematical Reviews  
This paper is concerned with the convergence of abstract itera- tion schemes for a general algorithm model involving point-to- set mappings f,: X*+!  ...  ., another paper of Torn [in Toward global optimization 2, 49- 62, North-Holland, Amsterdam, 1978; RZhMat 1980:3 V846]); (3) a systematic evolution of a complex of points spanning the space, in the direction  ... 

Memes Evolution in a Memetic Variant of Particle Swarm Optimization

Umberto Bartoccini, Arturo Carpi, Valentina Poggioni, Valentino Santucci
2019 Mathematics  
In this work, a coevolving memetic particle swarm optimization (CoMPSO) algorithm is presented.  ...  Preliminary experimental results show that CoMPSO is competitive with respect to standard PSO and other memetic PSO schemes in literature, and its a promising starting point for further research in adaptive  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math7050423 fatcat:hzaqynsixvft7hfmqxttqcploy

The gradient projection algorithm with adaptive mutation step length for non-probabilistic reliability index

2017 Tehnički Vjesnik  
Original scientific paper Aiming at the problems of selection parameter step-size and premature convergence that occurred when searching the local area in the optimal design of adaptive gradient projection  ...  algorithm in this paper, adaptive variable step-size mechanism strategy and adaptive variable step-size mechanism were established.  ...  Acknowledgements This work was funded by The National Natural Science Foundation of China (No. 51465017). References  ... 
doi:10.17559/tv-20160502062504 fatcat:tz3mcv2obrdglnemcnnmail6ia

A new adaptive broadcasting approach for mobile ad hoc networks

Mustsfa Bani Khalaf, Ahmed Y. Al-Dubai, William Buchanan
2010 2010 Wireless Advanced 2010  
Under the umbrella of this scheme, many dynamic probabilistic broadcasting algorithms have been proposed in the literature to solve the BSP.  ...  In an attempt to enhance and promote the quality of the probabilistic scheme, this paper proposes a new probabilistic approach to overcome these limitations.  ...  Our adaptive approachwork proposes a new algorithm to handle the weakness of existing probabilistic schemes. We incorporate these algorithms with AODV and evaluate its performance by using NS-2.34.  ... 
doi:10.1109/wiad.2010.5544944 fatcat:3pyjev6uezgdzpyhhb2b5zlunq

Genetic Algorithm with adaptive elitist-population strategies for multimodal function optimization

Yong Liang, Kwong-Sak Leung
2011 Applied Soft Computing  
Incorporation of the new multimodal technique in any known evolutionary algorithm leads to a multimodal version of the algorithm.  ...  AEGA has been shown to be very efficient and effective in finding multiple solutions of complicated benchmark and real-world multimodal optimization problems.  ...  Acknowledgments This research was partially supported by RGC Research Grant GRF 414708 of Hong Kong SAR and Macau Science and Technology Develop Fund (Grant No. 021/2008/A) of Macau SAR.  ... 
doi:10.1016/j.asoc.2010.06.017 fatcat:fhxvgnupejdp5gtwfadjbdohvm

A constrained, globalized, and bounded Nelder?Mead method for engineering optimization

M.A. Luersen, R. Le Riche, F. Guyon
2004 Structural And Multidisciplinary Optimization  
One of the fundamental difficulties in engineering design is the multiplicity of local solutions. This has triggered much effort in the development of global search algorithms.  ...  Globalization is achieved by probabilistic restarts. A spacial probability of starting a local search is built based on past searches. An improved Nelder-Mead algorithm is the local optimizer.  ...  Acknowledgements The first author would like to express his thanks to the Federal Center for Technological Education of Paraná (CEFET-PR), Brazil, and to the Brazilian funding agency CNPq for financial  ... 
doi:10.1007/s00158-003-0320-9 fatcat:vqetd7juybcrbgbkgull4lq7iu


2008 International journal on artificial intelligence tools  
A new crossover technique for genetic algorithms is proposed in this paper. The technique is called probabilistic adaptive crossover and denoted by PAX.  ...  The method includes the estimation of the probability distribution of the population, in order to store in a unique probability vector P information about the best and the worse solutions of the problem  ...  Acknowledgments The results presented in this work were supported by CONYCIT-Chile, under the grant FONDEF D01-1016, "Chilean Red Wine Classification by means of Intelligent Instrumentation".  ... 
doi:10.1142/s0218213008004333 fatcat:7lqfz53lr5fv7kxppn5lf2e6li
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