Temat: meta-heuristic optimization - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Optimal point to point path planning of flexible manipulator under large deformation by using harmony search method
Autorzy:: Esfandiar, H.
Korayem, M. H.
Powiązania:: https://bibliotekanauki.pl/articles/280605.pdf
Data publikacji:: 2016
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:: meta-heuristic optimization
harmony search
large deformation
flexible manipulator
Opis:: This paper aims at planning an optimal point to point path for a flexible manipulator under large deformation. For this purpose, the researchers use a direct method and meta-heuristic optimization process. In this paper, the maximum load carried by the manipulator and the minimum transmission time are taken as objective functions of the optimization process to get optimal path profiles. Kinematic constraints, the maximum velocity and acceleration, the dynamic constraint of the maximum torque applied to the arms and also the constraint of final point accuracy are discussed. For the optimization process, the Harmony Search (HS) method is used. To evaluate the effectiveness of the approach proposed, simulation studies are reviewed by considering a two-link flexible manipulator with the fixed base. The findings indicate that the proposed method is in power of dealing with nonlinear dynamics of the system. Furthermore, the results obtained by rigid, small and large deformation models are compared with each other.
Źródło:: Journal of Theoretical and Applied Mechanics; 2016, 54, 1; 179-193
1429-2955
Pojawia się w:: Journal of Theoretical and Applied Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Metaheuristic optimization of marginal risk constrained long - short portfolios
Autorzy:: Vijayalakshmi Pai, G. A.
Michel, T.
Powiązania:: https://bibliotekanauki.pl/articles/91858.pdf
Data publikacji:: 2012
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: metaheuristic
optimization
portfolio optimization
marginal risk
quadratic programming
meta heuristic method
data envelopment analysis
Opis:: The problem of portfolio optimization with its twin objectives of maximizing expected portfolio return and minimizing portfolio risk renders itself difficult for direct solving using traditional methods when constraints reflective of investor preferences, risk management and market conditions are imposed on the underlying mathematical model. Marginal risk that represents the risk contributed by an asset to the total portfolio risk is an important criterion during portfolio selection and risk management. However, the inclusion of the constraint turns the problem model into a notorious non-convex quadratic constrained quadratic programming problem that seeks acceptable solutions using metaheuristic methods. In this work, two metaheuristic methods, viz., Evolution Strategy with Hall of Fame and Differential Evolution (rand/1/bin) with Hall of Fame have been evolved to solve the complex problem and compare the quality of the solutions obtained. The experimental studies have been undertaken on the Bombay Stock Exchange (BSE200) data set for the period March 1999-March 2009. The efficiency of the portfolios obtained by the two metaheuristic methods have been analyzed using Data Envelopment Analysis.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 3; 259-274
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Modified blind naked mole-rat algorithm applied to electromagnetic design problems
Autorzy:: Taherdangkoo, Mohammad
Powiązania:: https://bibliotekanauki.pl/articles/1841273.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: electromagnetic design problems
global optimization
meta-heuristic algorithm
problemy z projektowaniem elektromagnetycznym
globalna optymalizacja
algorytm metaheurystyczny
Opis:: In this paper,we proposed a modified meta-heuristic algorithm based on the blind naked mole-rat (BNMR) algorithm to solve the multiple standard benchmark problems. We then apply the proposed algorithm to solve an engineering inverse problem in the electromagnetic field to validate the results. The main objective is to modify the BNMR algorithm by employing two different types of distribution processes to improve the search strategy. Furthermore, we proposed an improvement scheme for the objective function and we have changed some parameters in the implementation of the BNMR algorithm. The performance of the BNMR algorithm was improved by introducing several new parameters to find the better target resources in the implementation of a modified BNMR algorithm. The results demonstrate that the changed candidate solutions fall into the neighborhood of the real solution. The results show the superiority of the propose method over other methods in solving various mathematical and electromagnetic problems.
Źródło:: Archives of Electrical Engineering; 2021, 70, 2; 167-380
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: A novel variant of the salp swarm algorithm for engineering optimization
Autorzy:: Jia, Fuyun
Luo, Sheng
Yin, Guan
Ye, Yin
Powiązania:: https://bibliotekanauki.pl/articles/23944824.pdf
Data publikacji:: 2023
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: salp swarm algorithm
meta-heuristic algorithm
chaos theory
sine-cosine mechanism
quantum computation
optimization design of engineering
Opis:: There are many design problems need to be optimized in various fields of engineering, and most of them belong to the NP-hard problem. The meta-heuristic algorithm is one kind of optimization method and provides an effective way to solve the NP-hard problem. Salp swarm algorithm (SSA) is a nature-inspired algorithm that mimics and mathematically models the behavior of slap swarm in nature. However, similar to most of the meta-heuristic algorithms, the traditional SSA has some shortcomings, such as entrapment in local optima. In this paper, the three main strategies are adopted to strengthen the basic SSA, including chaos theory, sine-cosine mechanism and the principle of quantum computation. Therefore, the SSA variant is proposed in this research, namely SCQ-SSA. The representative benchmark functions are employed to test the performances of the algorithms. The SCQ-SSA are compared with the seven algorithms in high-dimensional functions (1000 dimensions), seven SSA variants and six advanced variants on benchmark functions, the experiment reveals that the SCQ-SSA enhances resulting precision and alleviates local optimal problems. Besides, the SCQ-SSA is applied to resolve three classical engineering problems: tubular column design problem, tension/compression spring design problem and pressure vessel design problem. The design results indicate that these engineering problems are optimized with high accuracy and superiority by the improved SSA. The source code is available in the URL: https://github.com/ye-zero/SCQSSA/tree/main/SCQ-SSA.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 3; 131--149
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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