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1.
Population size reduction for the differential evolution algorithm
Janez Brest, Mirjam Sepesy Maučec, 2008, izvirni znanstveni članek

Opis: This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.
Ključne besede: differential evolution, control parameter, fitness function, global function optimization, self-adaptation, population size
Objavljeno: 01.06.2012; Ogledov: 1174; Prenosov: 59
URL Povezava na celotno besedilo

2.
Performance comparison of self-adaptive and adaptive differential evolution algorithms
Janez Brest, Borko Bošković, Sašo Greiner, Viljem Žumer, Mirjam Sepesy Maučec, 2007, izvirni znanstveni članek

Opis: Differential evolution (DE) has been shown to be a simple, yet powerful, evolutionary algorithm for global optimization. for many real problems. Adaptation, especially self-adaptation, has been found to be highly beneficial for adjusting control parameters, especially when done without any user interaction. This paper presents differential evolution algorithms, whichuse different adaptive or self-adaptive mechanisms applied to the control parameters. Detailed performance comparisons of these algorithms on the benchmark functions are outlined.
Ključne besede: differential evolution, control parameter, fitness function, optimization, self-adaption
Objavljeno: 01.06.2012; Ogledov: 1236; Prenosov: 51
URL Povezava na celotno besedilo

3.
Optimization of energy storage usage
Arnel Glotić, Peter Kitak, Igor Tičar, Adnan Glotić, 2012, objavljeni znanstveni prispevek na konferenci

Opis: This paper suggests the use of dynamic population size throughout the optimization process which is applied on the numerical model of a medium voltage post insulator. The main objective of the dynamic population is reducing population size, to achieve faster convergence. Change of population size can be done in any iteration by proposed method. The multiobjective optimization process is based on the PSO algorithm, which is suitably modifiedin order to operate with the principle of the optimal Pareto front.
Ključne besede: differential evolution, energy, optimization, hydro power plants
Objavljeno: 10.07.2015; Ogledov: 460; Prenosov: 23
URL Povezava na celotno besedilo

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A hybrid bat algorithm
Iztok Fister, Dušan Fister, Xin-She Yang, 2013, izvirni znanstveni članek

Ključne besede: swarm intelligence, bat algorithm, differential evolution, optimization
Objavljeno: 21.12.2015; Ogledov: 782; Prenosov: 7
URL Povezava na celotno besedilo

7.
Optimal robust motion controller design using multi-objective genetic algorithm
Andrej Sarjaš, Rajko Svečko, Amor Chowdhury, 2014, izvirni znanstveni članek

Opis: This paper describes the use of a multi-objective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with non-negativity conditions. Regional pole placement method is presented with the aims of controllers% structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multi-objective function is composed of different unrelated criteria such as, robust stability, controllers' stability and time performance indexes of closed loops. The design of controllers and multi-objective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm - Differential evolution.
Ključne besede: disturbance observer, DOB, uncertainty systems, optimal robust control, multi-objective optimization, differential evolution
Objavljeno: 15.06.2017; Ogledov: 405; Prenosov: 190
.pdf Celotno besedilo (2,22 MB)
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8.
Differential evolution and large-scale optimization applications
Aleš Zamuda, raziskovalni ali dokumentarni film, zvočna ali video publikacija

Opis: Differential Evolution (DE) is one of the most popular, high-performance optimization algorithms with variants that have been outperforming others for years. As a result, DE has grown to accommodate wide usage for a variety of disciplines across scientific fields. Differential Evolution and Large-Scale Optimization Applications presents a research-based overview and cross-disciplinary applications of optimization algorithms. Emphasizing applications of Differential Evolution (DE) across sectors and laying the foundation for further use of DE algorithms in real-world settings, this video is an essential resource for researchers, engineers, and graduate-level students. Topics Covered : Algorithms, Optimization, Parallel Differential Evolution, Performance Improvement, Stochastic Methods, Tree Model Reconstruction.
Ključne besede: differential Evolution, optimization, algorithms, stochastic methods, tree models, tree model reconstruction
Objavljeno: 14.05.2019; Ogledov: 166; Prenosov: 104
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