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Opposition based Chaotic Differential Evolution algorithm for solving global optimization problems
2012
2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)
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The proposed OCDE algorithm is different from basic DE in two aspects. ...
The numerical results obtained by OCDE when compared with the results obtained by DE and ODE (opposition based DE) algorithms on eighteen benchmark function demonstrate that the OCDE is able to find a ...
Selection is the step to choose the vector by holding a tournament between the target vector and the corresponding trial vector with the aim of creating an individual for the next generation. ...
doi:10.1109/nabic.2012.6402168
dblp:conf/nabic/ThangarajPCA12
fatcat:zsmexoff5nawnjyzkptm7twtpe
Numerical awareness in control
2004
IEEE Control Systems
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In papers dealing with methods for systems and control, we often observe a level of naivete concerning basic numerical issues related to algorithm development. ...
T here is a continuing and growing need in the systems and control community for good algorithms and robust numerical software for increasingly challenging applications. ...
This article identifies the general principles that lead to numerically reliable algorithms for solving a large collection of control problems. ...
doi:10.1109/mcs.2004.1272742
fatcat:23jcim7yzzh4roloyiewxk5auq
A Basic Algorithm for Generating Individualized Numerical Scale (BAGINS)
[article]
2022
arXiv
pre-print
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There is a growing interest in scale individualization rather than relying on a generic fixed scale since the perceptions of the decision maker regarding these linguistic labels are highly subjective. ...
To assess the value of scale individualization in general, and the performance of the proposed novel approach in particular, numerical and two empirical studies are conducted. ...
Algorithm 1 Basic Algorithm for Generating Individualized Numerical Scale (BAGINS) 1: Let S = (S k | k = 1, 2, ..., m) 2: Elicit L = (l ij ) n×n where l ij ∈ S 3: Construct A = (a ij ) n×n such that A ...
arXiv:2211.08740v1
fatcat:7wynbae5bjfmxnzyk2udajom4e
An Effective Hybrid Self-Adapting Differential Evolution Algorithm for the Joint Replenishment and Location-Inventory Problem in a Three-Level Supply Chain
2013
The Scientific World Journal
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To find an effective approach for the JR-LIP, a hybrid self-adapting differential evolution algorithm (HSDE) is designed. ...
In this paper, we provide an effective intelligent algorithm for a modified joint replenishment and location-inventory problem (JR-LIP). ...
Acknowledgments The authors are very grateful for the constructive comments of editors and referees. This ...
doi:10.1155/2013/270249
pmid:24453822
pmcid:PMC3878286
fatcat:hahtltu2yralrgcow3j6tbhhmq
Diagonal Scaling of Ill-Conditioned Matrixes by Genetic Algorithm
2012
Journal of Applied Mathematics, Statistics and Informatics
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Diagonal Scaling of Ill-Conditioned Matrixes by Genetic Algorithm The purpose of this article is to use genetic algorithm for finding two invertible diagonal matrices D1 and D2 such that the scaled matrix ...
A genetic algorithm starts by generating a number of possible solutions to a problem, evaluates them and applies the basic genetic operators to that initial population according to the individual fitness ...
Although there are more elaborate versions of these operators, the basic principles remain similar for most Genetic algorithms. ...
doi:10.2478/v10294-012-0005-3
fatcat:roimcyauzncahke2el3m5cr66a
Guest Editors' Introduction: Multigrid Computing
2006
Computing in science & engineering (Print)
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M ultigrid methods are among the most important algorithms for computational scientists because they're the most efficient solvers for a wide range of problems. ...
equations (PDEs) and the linear systems that arise when they're discretized, the basic multigrid principle of coupling multiple scales has much wider applicability. ...
Thus, we can't easily use it as a generic linear solver-rather, we often have to customize it for each individual problem. ...
doi:10.1109/mcse.2006.109
fatcat:uas2az2i3ndwniygxmedk44d7m
New mutation schemes for differential evolution algorithm and their application to the optimization of directional over-current relay settings
2010
Applied Mathematics and Computation
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In the present study we propose five new mutation schemes for the basic DE algorithm. The corresponding versions are termed as MDE1, MDE2, MDE3, MDE4 and MDE5. ...
These new schemes make use of the absolute weighted difference between the two points and instead of using a fixed scaling factor F, use a scaling factor following the Laplace distribution. ...
The second function is a simple sphere function which is strictly convex and unimodal and is generally considered as a good starting point for testing an optimization algorithm. ...
doi:10.1016/j.amc.2010.01.071
fatcat:fc6wlecqwfghtfapfcf2gbmcie
Multi-objective Optimization Based on Improved Differential Evolution Algorithm
2014
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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Meanwhile, a random mutation mechanism is adopted to process individuals that show stagnation behaviour. ...
After that, a series of frequently-used benchmark test functions are used to test the performance of the fundamental and improved DE algorithms. ...
Secondly, the paper makes an numerical experiment on the performance of the improved algorithms and makes a comparative analysis. ...
doi:10.12928/telkomnika.v12i4.531
fatcat:6scl2yva75fplh4r2t4mdo2dta
Genetic Algorithm for Multidimensional Scaling over Mixed and Incomplete Data
[chapter]
2012
Lecture Notes in Computer Science
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For this reason, in this paper we propose a genetic algorithm especially designed for multidimensional scaling over mixed and incomplete data. ...
Some experiments using datasets from the UCI repository, and a comparison against a common algorithm for multidimensional scaling, shows the behavior of our proposal. ...
Algorithm 1 shows the generic genetic algorithm used in this work, which is based on the basic genetic algorithms [14] . ...
doi:10.1007/978-3-642-31149-9_23
fatcat:n6lrrkwszbf5pjessk532fsqmm
An analysis of the behavior of simplified evolutionary algorithms on trap functions
2003
IEEE Transactions on Evolutionary Computation
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Methods are developed to numerically analyze an evolutionary algorithm (EA) that applies mutation and selection on a bit-string representation to find the optimum for a bimodal unitation function called ...
As a main result of this analysis, a new so-called (1 : )-EA is proposed, which generates offspring using individual mutation rates . ...
This algorithm is a very simplified version of an EA. We use this algorithm to introduce an extension of an ordinary EA: different fixed mutation rates are used to generate children. ...
doi:10.1109/tevc.2002.806169
fatcat:vfpgrhzie5hslj6ylhqefviexa
Metamodel-Based Optimization of the Labyrinth Seal
2017
Archive of Mechanical Engineering
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Due to the complexity of the problem and for the sake of the computation time, a decision was made to modify the standard evolutionary optimization algorithm by adding an approach based on a metamodel. ...
It then complements the next generation of the evolutionary algorithm. ...
Here, the developed algorithm is based on a traditional genetic algorithm, where some individuals are generated additionally using a metamodel based on an artificial Neural Network. ...
doi:10.1515/meceng-2017-0005
fatcat:oj3reoztr5fc3jux3cip6ie7zq
A Novel Cloud Evolutionary Strategy for Ackley's Function
2017
DEStech Transactions on Engineering and Technology Research
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than standard genetic algorithm or a kind of optimization algorithm based on the genetic algorithm and nonlinear programming in the convergence speed and search accuracy. ...
This paper proposes a novel evolutionary strategy based on cloud model, and applies it to solving the well-known multi-modal Ackley's problem.The results indicate that cloud evolutionary strategy is better ...
For the sake of comparing and analysising, set the total number of individuals of each generation n = 20, community richness m=10, the populations scale PS=(6,4,3,1,1,1,1,1,1,1), λ= 3, K = 4, L= 2, and ...
doi:10.12783/dtetr/sste2016/6518
fatcat:rtiduev5jbcm7mmds4shlg26ly
Computation in Large-Scale Scientific and Internet Data Applications is a Focus of MMDS 2010
[article]
2010
arXiv
pre-print
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; and the second, MMDS 2008, explored more generally fundamental algorithmic and statistical challenges in modern large-scale data analysis. ...
The 2010 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2010) was held at Stanford University, June 15--18. ...
Acknowledgments I am grateful to the numerous individuals who provided assistance prior to and during MMDS 2010; to my co-organizers Alex Shkolnik, Petros Drineas, Lek-Heng Lim, Gunnar Carlsson; and to ...
arXiv:1012.4231v1
fatcat:46lpcsxylbc7rhv5cr336bdvdm
A simple adaptive Differential Evolution algorithm
2009
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC)
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DE is generally considered as a reliable, accurate, robust and fast optimization techniques. ...
Differential Evolution (DE) is a simple and efficient scheme for global optimization over continuous spaces. ...
In this way individuals in a new generation are as good as or better than the individuals in the previous generation.
IV. ...
doi:10.1109/nabic.2009.5393350
dblp:conf/nabic/ThangarajPA09a
fatcat:5od2zuwihbctha2nt2v5whhnmm
Genetic Algorithm And Padé-Moment Matching For Model Order Reduction
2015
Zenodo
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A mixed method for model order reduction is presented in this paper. ...
The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. ...
Selection Function To produce successive generations, selection of individuals plays a very significant role in a genetic algorithm. ...
doi:10.5281/zenodo.1109494
fatcat:mjynoxllzjgs3ilhwfinnygiau
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