Wyniki wyszukiwania - BazTech

1

A hybrid optimized resource allocation modelfor multi-cloud environment using batand particle swarm optimization algorithms

Selvapandian D., Santhosh R.

Computer Assisted Methods in Engineering and Science

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2022

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Vol. 29, no. 1-2 spec.

87--103

EN

In cloud computing, scheduling and resource allocation are the major factors that definethe overall quality of services. An efficient resource allocation module is required in cloudcomputing since resource allocation in a single cloud environment is a complex process.Whereas resource allocation in a multi-cloud environment further increases the complexityof allocation procedures. Earlier, resources from the multi-cloud environment were allocated based on task requirements. However, it is essential to analyze the present resourceavailability status and resource capability before allocating to the requested tasks. So, inthis research work, a hybrid optimized resource allocation model is presented using bat optimization algorithm and particle swarm optimization algorithm to allocate the resourceconsidering the resource status, distance, bandwidth, and task requirements. Proposedmodel performance is evaluated through simulation and compared with conventional optimization algorithms. For a set of 500 tasks, the proposed approach allocates resourcesin 47 s, with a minimum energy consumption of 200 kWh. Compared to conventionalapproaches, the performance of the proposed model is much better in terms of deadlinemissed tasks, resource requirement, energy consumption, and allocation time.

2

Optimization of material distribution for forged automotive components using hybrid optimization techniques

Sebastjan Przemysław, Kuś Wacław

Computer Methods in Materials Science

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2021

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Vol. 21, No. 2

63--74

EN

The paper deals with the problem of optimal material distribution inside the provided design area. Optimization based on deterministic and stochastic algorithms is used to obtain the best result on the basis of the proposed objective function and constraints. The optimization of the shock absorber is used as an example of the described methods. One of the main difficulties addressed is the manufacturability of the optimized part intended for the forging process. Additionally, nonlinear buckling simulation with the use of the finite element method is used to solve the misuse case of shock absorber compression, where the shape of the optimized part has a key role in the total strength of the automotive damper. All of that, together with the required design precision, creates the nontrivial constrained optimization problem solved using the parametric, implicit geometry representation and a combination of stochastic and deterministic algorithms used with parallel design processing. Two methods of optimization are examined and compared in terms of the total amount of function calls, final design mass, and feasibility of the resultant design. Also, the amount of parameters used for the implicit geometry representation is greatly reduced compared to existing schemes presented in the literature. The problem addressed in this article is strongly inspired by the actual industrial example of the mass minimization process, but it is more focused on the actual manufacturability of the resultant component and admissible solving time. Commercially accessible software combined with authors’ procedures is used to resolve the material distribution task, which makes the proposed method universal and easily adapted to other fields of the optimization of mechanical elements.

3

A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system

Mostafa Hazem H., Ibrahim Amr M., Anis Wagdi R.

Archives of Electrical Engineering

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2019

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Vol. 68, nr 3

611--627

EN

This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS- PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.

4

Hybrid optimization process applied to tuning of Dynamic Matrix Control: atudy case with DC motor

Carvalho D. F. de, Ganzaroli C. A., Couto L. do, Dias R. N. H. M., Calixto W. P.

Transactions on Environment and Electrical Engineering

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2017

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Vol. 2, No. 2

24--30

EN

This paper presents study about Dynamic Matrix Control (DMC) controller applied to speed control of DC motor. DMC controller parameters (prediction horizon, control horizon and damping rate of reference) are obtained through optimization methods employing heuristic, deterministic and hybrid strategies. The use of advanced control technique combined with using of optimization methods aims to achieve highly efficient control, reducing the transient state period and variations in steady state. These methods were applied on a simulation model in order to verify which one provides better control results.

5

Hybridization of the optimization process as an alternative way to find approximate solutions for NP-hard problems

Rozenberg L., Rychcicki R.

Przegląd Elektrotechniczny

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2015

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R. 91, nr 2

59-62

EN

This paper presents the results of calculations that demonstrate the possibility of using hybrid optimization method (with variable structure) for determining the approximate solutions to NP-hard problems. The Travelling Salesman Problem (TSP) is a classic combinatorial optimization subject, which has found widespread use in practice. Simple in definition, have remained hard to solve for many years. Not only an efficient solution would yield benefits in a substantial amount of routing problems, but it would also affect planning and logistics in a positive way.

PL

W prezentowanym artykule pokazano możliwość wykorzystania hybrydy optymalizacyjnej do uzyskania przybliżonego rozwiązania zadania NP-trudnego, czyli problemu obliczeniowego o ponad wykładniczym zapotrzebowaniu na moc obliczeniową. Do badań wybrano znany od wielu lat problem komiwojażera, którego od lat nie udało się ostatecznie rozwiązać. Wybór ten jednak umożliwił uzyskanie pokaźnego materiału porównawczego.

6

A hybrid algorithm for solving inverse problems in elasticity

Barabasz B., Gajda-Zagórska E., Migórski S., Paszyński M., Schaefer R., Smołka M.

International Journal of Applied Mathematics and Computer Science

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2014

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Vol. 24, no. 4

865--886

EN

The paper offers a new approach to handling difficult parametric inverse problems in elasticity and thermo-elasticity, formulated as global optimization ones. The proposed strategy is composed of two phases. In the first, global phase, the stochastic hp-HGS algorithm recognizes the basins of attraction of various objective minima. In the second phase, the local objective minimizers are closer approached by steepest descent processes executed singly in each basin of attraction. The proposed complex strategy is especially dedicated to ill-posed problems with multimodal objective functionals. The strategy offers comparatively low computational and memory costs resulting from a double-adaptive technique in both forward and inverse problem domains. We provide a result on the Lipschitz continuity of the objective functional composed of the elastic energy and the boundary displacement misfits with respect to the unknown constitutive parameters. It allows common scaling of the accuracy of solving forward and inverse problems, which is the core of the introduced double-adaptive technique. The capability of the proposed method of finding multiple solutions is illustrated by a computational example which consists in restoring all feasible Young modulus distributions minimizing an objective functional in a 3D domain of a photo polymer template obtained during step and flash imprint lithography.

7

Założenia hybrydowej metody optymalizacji funkcji w systemie wspomagania decyzji o strukturze rozproszonej

Twardochleb, Rychcicki

Metody Informatyki Stosowanej

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2011

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nr 1

169-181

EN

Classic optimization methods are bound to have many limitations. As a result, such methods are of ten not suitable for efficient problem solving. This paper puts forth aproposal for a new hybrid optimization method which combines together two basic methods, i.e. Monte Carlo method and Rosenbrock method. The combination produces a method that has all of its constituents' advantages, yet does not in herit any oft heir drawbacks, resulting in higher convergence rates and greater computation speeds. Due to its simplified approach towards modeling, our method can be easily adapted to parallel or distributed computing systems, enabling researchers to use clusters consisting of many separate machines. Those clusters can provide the computational power needed to solve complicated optimization problems..

8

Hybrid optimization algorithm using evolutionary algorithm and local search method with its application in digital FIR filter design

Adamski K.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2008

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z. 165

23-32

EN

This paper is devoted to the application of an Evolutionary Algorithm to the design of Finite Impulse Response filters (FIR). A hybrid algorithm is proposed, which consists of a robust global optimization method (Evolutionary Algorithm - EA) and a good local optimization method (Quasi-Newton - QN). An experimental comparison of the hybrid algorithm against EA and QN alone indicates that EA yields filters with the better amplitude characteristics than QN. Furthermore the hybrid method yields filters with even better amplitude characteristics and in some times, it needs significantly less time than EA alone to reach good solutions.

9

Hybrydowa optymalizacja topologiczna dynamicznych układów mechanicznych

Burczyński T., Orantek P.

Zeszyty Naukowe Politechniki Rzeszowskiej. Mechanika

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2005

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z. 65 [222]

53--60

EN

In this paper scientific research on using the hybrid algorithm in optimization of the dynamic structures was carried out. The boundary-initial problem for elastodynamics was solved by using boundary element method (BEM) [2]. The hybrid algorithm being the coupling of the evolutionary algorithm, gradient algorithm and the artificial neural network was carried out. Topology and shape optimization problems were considered for different criteria, which concern: mass, displacements, stresses, compliance and natural frequencies. As a tool for the modeling of boundary shape the NURBS curves were applied. Several numerical examples testifying to the effectiveness and efficiency of the proposed methods of optimization were carried out, a few interesting tests are included in the paper.