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Large Scale Global Optimization by Hybrid Evolutionary Computation [article]

Gutha Jaya Krishna, Vadlamani Ravi
2019 arXiv   pre-print
variables, of the CEC 2013 LSGO special session.  ...  The Congress on Evolutionary Computation (CEC) began an LSGO competition to come up with algorithms with a bunch of standard benchmark unconstrained LSGO functions.  ...  The proposed algorithm are compared with the winners of the CEC 2010 LSGO, SOCO 2011, CEC 2012 LSGO and CEC 2013 LSGO competitions on the CEC 2013 LSGO benchmarks.  ... 
arXiv:1910.03799v1 fatcat:pfk7tp6mbngpphwcslo2eruoum

New Variants of Adaptive Differential Evolution Algorithm with Competing Strategies

Petr Bujok, Josef Tvrdík
2015 Acta Electrotechnica et Informatica  
New variants of the adaptive competitive differential evolution algorithm are proposed and tested experimentally on the CEC 2013 test suite.  ...  The aim of the experimental comparison is to find whether the presence of the current-to-pbest mutation strategy increases the efficiency of the differential evolution algorithm, especially on rotated  ...  Success-history based parameter adaptation for differential evolution. In 2013 [12] TVRDÍK, J. Self-adaptive variants of differential evolution with exponential crossover.  ... 
doi:10.15546/aeei-2015-0018 fatcat:ic6nrwgrgfe2jhpgk7cxjvrocu

Real Parameter Single Objective Optimization using self-adaptive differential evolution algorithm with more strategies

Janez Brest, Borko Boskovic, Ales Zamuda, Iztok Fister, Efren Mezura-Montes
2013 2013 IEEE Congress on Evolutionary Computation  
A new differential evolution algorithm for single objective optimization is presented in this paper.  ...  The experimental results obtained by our algorithm on the benchmark consisting of 25 test functions with dimensions D = 10, D = 30, and D = 50 as provided for the CEC 2013 competition and special session  ...  A self-adaptive jDE algorithm was introduced in 2006 [11] . jDE-based algorithms were applied to solve large-scale single objective optimization problems: CEC 2008 [15] , CEC 2010 [16] , CEC 2012 [  ... 
doi:10.1109/cec.2013.6557594 dblp:conf/cec/BrestBZFM13 fatcat:ddh3v7sihzhanix6wvwhszxnju

A Survey on Metaheuristics for Solving Large Scale Optimization Problems

Atinesh Singh, Nanda Dulal
2017 International Journal of Computer Applications  
In the research community, they are generally labeled as Large Scale Global Optimization (LSGO) problems. Several Metaheuristics has been proposed to tackle these problems.  ...  This paper gives a brief introduction of some state-of-the-art Metaheuristics used in the field of LSGO, discusses their performance in CEC Competition on LSGO and finally, future scope in this field is  ...  Adaptive weighting strategy applies a weight to each of the sub-component after every cycle, and then evolves the weight vector with Differential Evolution.  ... 
doi:10.5120/ijca2017914839 fatcat:2lhciqf4lbgetpyeouf5xykps4

Adaptive multi-population inflationary differential evolution

Marilena Di Carlo, Massimiliano Vasile, Edmondo Minisci
2019 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Inflationary differential evolution algorithm (IDEA) combines basic differential evolution (DE) with some of the restart and local search mechanisms of Monotonic Basin Hopping (MBH).  ...  Introduction Differential evolution (DE), proposed by Price et al. (2006) , is a well-known population-based evolutionary algorithm for solving global optimisation problems over continuous spaces.  ...  CEC 2014 test set In line with the rules of the CEC 2014 competition (Liang et al. 2013 ), MP-AIDEA was applied to the solution of the functions in the CEC 2014 test set in dimension n D = 10, 30, 50  ... 
doi:10.1007/s00500-019-04154-5 fatcat:rzqmuo7vbbfsddh25h4qrpcfua

LSHADE Algorithm with a Rank-based Selective Pressure Strategy for the Circular Antenna Array Design Problem

Shakhnaz Akhmedova, Vladimir Stanovov, Eugene Semenkin
2018 Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics  
LSHADE-RSP is built to tackle complex high-dimensional global optimization problems, and firstly it has been successfully tested on the CEC 2018 benchmark functions.  ...  A new algorithm called LSHADE-RSP, which is based on a modification of the Differential Evolution technique, namely the LSHADE algorithm, with a rank-based selective pressure strategy, is presented in  ...  Finally, some conclusions are given in the last section DIFFERENTIAL EVOLUTION Differential evolution (DE) is a global optimization evolutionary meta-heuristic first introduced in 1997 for solving continuous  ... 
doi:10.5220/0006852501590165 dblp:conf/icinco/AkhmedovaSS18 fatcat:eyyi4wjk2be4xdlgmara7l5yna

Reflected Adaptive Differential Evolution with Two External Archives for Large-Scale Global Optimization

Rashida Adeeb, Nasser Tairan, Muhammad Asif, Wali Khan, Abdel Salhi
2016 International Journal of Advanced Computer Science and Applications  
JADE is an adaptive scheme of nature inspired algorithm, Differential Evolution (DE). It performed considerably improved on a set of well-studied benchmark test problems.  ...  In this paper, we evaluate the performance of new JADE with two external archives to deal with unconstrained continuous large-scale global optimization problems labeled as Reflected Adaptive Differential  ...  DIFFERENTIAL EVOLUTION AND JADE A.  ... 
doi:10.14569/ijacsa.2016.070284 fatcat:5kpyhg33znbzzagkaqufr7ateu

A self adaptive hybrid artificial bee colony algorithm for solving CEC 2013 real-parameter optimization problems

Hai Shan, Toshiyuki Yasuda, Kazuhiro Ohkura
2013 Proceedings of the 2013 IEEE/SICE International Symposium on System Integration  
optimization problems based on 28 benchmark functions defined by IEEE Congress on Evolutionary Computation (CEC) 2013 test suite with all the dimension size of 10, 30, and 50, respectively.  ...  To evaluate the performance of the standard ABC, the proposed ABC, differential evolution (DE) and particle swarm optimization (PSO) algorithms, we implemented the experiments of real parameter numerical  ...  Experimental Setup The CEC 2013 test suite extends its predecessor CEC 2005 test suite.  ... 
doi:10.1109/sii.2013.6776717 dblp:conf/sii/ShanYO13 fatcat:cvrct2h3drc45gzwh2b7nvdqjm

A Three-level Recursive Differential Grouping Method for Large-scale Continuous Optimization

Hong-bin Xu, Fei Li, Hao Shen
2020 IEEE Access  
Cooperative co-evolution (CC) is widely used to solve large-scale continuous optimization problems, which divides a large-scale problem into several small-scale sub-problems via decomposition methods and  ...  Furthermore, TRDG is embedded into two frameworks to tackle CEC'2010 large-scale continuous optimization problems.  ...  CEC'2010 AND CEC'2013 BENCHMARK FUNCTIONS CEC'2010 benchmark functions [32] were proposed by the IEEE CEC'2010 special meeting for large-scale global optimization and related competitions.  ... 
doi:10.1109/access.2020.3013661 fatcat:5pqalfbylzdypfkywbiibyn6ee

A Modified Artificial Algae Algorithm For Large Scale Global Optimization Problems

Havva Gul Kocer, Sait Ali Uymaz
2018 International Journal of Intelligent Systems and Applications in Engineering  
Optimization technology is used to accelerate decision-making processes and to increase the quality of decision making in management and engineering problems.  ...  For the purpose, in this paper Modified Artificial Algae Algorithm (MAAA) is proposed by modifying original version of Artificial Algae Algorithm (AAA) inspiring by Differential Evolution Algorithm (DE  ...  Common rules and benchmark sets were presented in 2008, 2010 and 2013 to evaluate algorithms fairly in these competitions.  ... 
doi:10.18201/ijisae.2018448458 fatcat:gdygtvk25vfmbchbput6ot53kq

DG2: A Faster and More Accurate Differential Grouping for Large-Scale Black-Box Optimization

Mohammad Nabi Omidvar, Ming Yang, Yi Mei, Xiaodong Li, Xin Yao
2017 IEEE Transactions on Evolutionary Computation  
SOFTWARE IMPLEMENTATION The MATLAB/Octave and C++ implementations of the DG2 algorithm can be accessed from the following link: https://bitbucket.org/mno/differential-grouping2  ...  MOS and MA-SW-Chains ranked first in the CEC'2013 and CEC'2010 competition on large-scale optimization respectively.  ...  Finally, we have shown empirically that in conjunction with DG2, the contribution-based cooperative co-evolution performs as well as the top performers of the CEC'2010 and CEC'2013 competition on large-scale  ... 
doi:10.1109/tevc.2017.2694221 fatcat:ssyk7ehn7jdytkf63ewzg3gcyi

Real Parameter Optimization Using Levy Distributed Differential Evolution [chapter]

Nanda Dulal Jana, Aditya Narayn Hati, Rajkumar Darbar, Jaya Sil
2013 Lecture Notes in Computer Science  
Differential Evolution (DE) algorithm is a real parameter encoded evolutionary algorithm for global optimization. In this paper, Levy distributed DE (LevyDE) has been proposed.  ...  of CEC'05 benchmark functions.  ...  Differential Evolution Algorithm Differential Evolution (DE) is a stochastic, population-based optimization algorithm which was proposed by Storn and Price in 1996 [1] .  ... 
doi:10.1007/978-3-642-45062-4_85 fatcat:srq2wgqnwzdv7mcijzesc2haiq

Differential evolution on the CEC-2013 single-objective continuous optimization testbed

A. K. Qin, Xiaodong Li
2013 2013 IEEE Congress on Evolutionary Computation  
Differential evolution (DE) is one of the most powerful continuous optimizers in the field of evolutionary computation.  ...  This work systematically benchmarks a classic DE algorithm (DE/rand/1/bin) on the CEC-2013 single-objective continuous optimization testbed.  ...  According to the protocol of the CEC-2013 testbed [16] , two stopping criteria are applied: (1) the maximum number of function evaluations (maxFEvals) is reached where maxFEvals is set to 10 4 times problem  ... 
doi:10.1109/cec.2013.6557689 dblp:conf/cec/QinL13 fatcat:55rwckwtdrhntiw5fn2xdxcf7y

Understanding the problem space in single-objective numerical optimization using exploratory landscape analysis

Urban Škvorc, Tome Eftimov, Peter Korošec
2020 Applied Soft Computing  
The proposed method is evaluated on a set of benchmark problems taken from two well known state-of-the-art real-parameter single objective optimization benchmarks: the CEC Special Sessions and Competitions  ...  However, this step is also one of the hardest, as it can be difficult to determine how to evaluate the quality of the chosen problem set.  ...  We used Differential Evolution [34] as implemented in the R library DEoptim [35] with default parameters to optimize the factors for scaling and shifting transformations.  ... 
doi:10.1016/j.asoc.2020.106138 fatcat:pytc2c35wbhtfl5ohh5pqcur7e

An Improved LSHADE-RSP Algorithm with the Cauchy Perturbation: iLSHADE-RSP [article]

Tae Jong Choi, Chang Wook Ahn
2020 arXiv   pre-print
We applied the proposed approach to LSHADE-RSP ranked second place in the CEC 2018 competition on single objective real-valued optimization.  ...  A new method for improving the optimization performance of a state-of-the-art differential evolution (DE) variant is proposed in this paper.  ...  We applied the proposed approach to LSHADE-RSP ranked second place in the CEC 2018 competition on single objective real-valued optimization.  ... 
arXiv:2006.02591v1 fatcat:6pqcxpnc55e57bkms6oppv2vem
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