scholarly journals A Multi-Objective Differential Evolutionary Optimization Method for Performance Optimization of Cloud Application

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Performance Optimization ◽  
Search Space ◽  
Optimization Method ◽  
Performance Ratio ◽  
Cost Performance ◽  
Cloud Resource ◽  
Cloud Application ◽  
Problem Instances ◽  
Evolutionary Operators ◽  
Cloud Applications

Due to the limited search space in the existing performance optimization ap-proaches at software architectures of cloud applications (SAoCA) level, it is difficult for these methods to obtain the cloud resource usage scheme with optimal cost-performance ratio. Aiming at this problem, this paper firstly de-fines a performance optimization model called CAPOM that can enlarge the search space effectively. Secondly, an efficient differential evolutionary op-timization algorithm named MODE4CA is proposed to solve the CAPOM model by defining evolutionary operators with strategy pool and repair mechanism. Further, a method for optimizing performance at SAoCA level, called POM4CA is derived. Finally, two problem instances with different sizes are taken to conduct the experiments for comparing POM4CA with the current representative method under the light and heavy workload. The ex-perimental results show that POM4CA method can obtain better response time and spend less cost of cloud resources.

scholarly journals Roughing Milling with Ceramic Tools in Comparison with Sintered Carbide on Nickel-Based Alloys

Coatings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 734
Author(s):  
Pablo Fernández-Lucio ◽  
Octavio Pereira Neto ◽  
Gaizka Gómez-Escudero ◽  
Francisco Javier Amigo Fuertes ◽  
Asier Fernández Valdivielso ◽  
...  
Keyword(s):  
Cutting Speed ◽  
High Volume ◽  
Cemented Carbide ◽  
Performance Ratio ◽  
Cost Performance ◽  
Ceramic Tools ◽  
The Cost ◽  
Engine Components ◽  
Coated Carbide ◽  
Milling Tools

Productivity in the manufacture of aircrafts components, especially engine components, must increase along with more sustainable conditions. Regarding machining, a solution is proposed to increase the cutting speed, but engines are made with very difficult-to-cut alloys. In this work, a comparison between two cutting tool materials, namely (a) cemented carbide and (b) SiAlON ceramics, for milling rough operations in Inconel® 718 in aged condition was carried out. Furthermore, both the influence of coatings in cemented carbide milling tools and the cutting speed in the ceramic tools were analysed. All tools were tested until the end of their useful life. The cost performance ratio was used to compare the productivity of the tested tools. Despite the results showing higher durability of the coated carbide tool, the ceramic tools presented a better behavior in terms of productivity at higher speed. Therefore, ceramic tools should be used for higher productivity demands, while coated carbide tools for low speed-high volume material removal.

scholarly journals In-Orbit Operational Parameter Calculation and Performance Optimization in KOMPSAT-6 Synthetic Aperture Radar

2021 ◽  
Vol 13 (12) ◽  
pp. 2342
Author(s):  
Jin-Bong Sung ◽  
Sung-Yong Hong
Keyword(s):  
Synthetic Aperture Radar ◽  
Performance Optimization ◽  
Pulse Repetition Frequency ◽  
Optimization Method ◽  
Synthetic Aperture ◽  
Operational Parameters ◽  
Operational Parameter ◽  
Design Methodologies ◽  
And Performance ◽  
Aperture Radar

A new method to design in-orbit synthetic aperture radar operational parameters has been implemented for the Korean Multi-purpose Satellite 6 mission. The implemented method optimizes the pulse repetition frequency when a satellite altitude changes from its nominal one, so it has the advantage that the synthetic aperture radar performances can satisfy the requirements for the in-orbit operation. Other commanding parameters have been designed to conduct trade-off between those parameters. This paper presents the new optimization method to maintain the synthetic aperture radar performances even in the case of an altitude variation. Design methodologies to determine operational parameters, respectively, at nominal altitude and in orbit are presented. In addition, numerical simulation is presented to validate the proposed optimization and the design methodologies.

scholarly journals A Fast Optimization Method for Reliability and Performance of Cloud Services Composition Application

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Wu ◽  
Naixue Xiong ◽  
Yannong Huang ◽  
Qiong Gu ◽  
Chunyang Hu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
State Space ◽  
Generating Function ◽  
Performance Optimization ◽  
Optimization Method ◽  
Cloud Services ◽  
Services Composition ◽  
Fast Optimization ◽  
And Performance ◽  
Universal Generating Function

At present the cloud computing is one of the newest trends of distributed computation, which is propelling another important revolution of software industry. The cloud services composition is one of the key techniques in software development. The optimization for reliability and performance of cloud services composition application, which is a typical stochastic optimization problem, is confronted with severe challenges due to its randomness and long transaction, as well as the characteristics of the cloud computing resources such as openness and dynamic. The traditional reliability and performance optimization techniques, for example, Markov model and state space analysis and so forth, have some defects such as being too time consuming and easy to cause state space explosion and unsatisfied the assumptions of component execution independence. To overcome these defects, we propose a fast optimization method for reliability and performance of cloud services composition application based on universal generating function and genetic algorithm in this paper. At first, a reliability and performance model for cloud service composition application based on the multiple state system theory is presented. Then the reliability and performance definition based on universal generating function is proposed. Based on this, a fast reliability and performance optimization algorithm is presented. In the end, the illustrative examples are given.

scholarly journals Ls-II: An Improved Locust Search Algorithm for Solving Optimization Problems

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Octavio Camarena ◽  
Erik Cuevas ◽  
Marco Pérez-Cisneros ◽  
Fernando Fausto ◽  
Adrián González ◽  
...  
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Search Space ◽  
Optimization Method ◽  
Superior Performance ◽  
Solution Quality ◽  
Original Algorithm ◽  
Motion Models ◽  
Search Mechanism ◽  
Solitary Phase

The Locust Search (LS) algorithm is a swarm-based optimization method inspired in the natural behavior of the desert locust. LS considers the inclusion of two distinctive nature-inspired search mechanism, namely, their solitary phase and social phase operators. These interesting search schemes allow LS to overcome some of the difficulties that commonly affect other similar methods, such as premature convergence and the lack of diversity on solutions. Recently, computer vision experiments in insect tracking methods have conducted to the development of more accurate locust motion models than those produced by simple behavior observations. The most distinctive characteristic of such new models is the use of probabilities to emulate the locust decision process. In this paper, a modification to the original LS algorithm, referred to as LS-II, is proposed to better handle global optimization problems. In LS-II, the locust motion model of the original algorithm is modified incorporating the main characteristics of the new biological formulations. As a result, LS-II improves its original capacities of exploration and exploitation of the search space. In order to test its performance, the proposed LS-II method is compared against several the state-of-the-art evolutionary methods considering a set of benchmark functions and engineering problems. Experimental results demonstrate the superior performance of the proposed approach in terms of solution quality and robustness.

Design Optimization Method for MR-Brake Actuators

2011 ◽  
Author(s):  
Ozan G. Erol ◽  
Hakan Gurocak ◽  
Berk Gonenc
Keyword(s):  
Optimal Solution ◽  
Volume Ratio ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Friction Torque ◽  
Element Analysis ◽  
Taguchi Design Of Experiments ◽  
Variable Friction ◽  
Electronically Controllable

MR-brakes work by varying viscosity of a magnetorheological (MR) fluid inside the brake. This electronically controllable viscosity leads to variable friction torque generated by the actuator. A properly designed MR-brake can have a high torque-to-volume ratio which is quite desirable for an actuator. However, designing an MR-brake is a complex process as there are many parameters involved in the design which can affect the size and torque output significantly. The contribution of this study is a new design approach that combines the Taguchi design of experiments method with parameterized finite element analysis for optimization. Unlike the typical multivariate optimization methods, this approach can identify the dominant parameters of the design and allows the designer to only explore their interactions during the optimization process. This unique feature reduces the size of the search space and the time it takes to find an optimal solution. It normally takes about a week to design an MR-brake manually. Our interactive method allows the designer to finish the design in about two minutes. In this paper, we first present the details of the MR-brake design problem. This is followed by the details of our new approach. Next, we show how to design an MR-brake using this method. Prototype of a new brake was fabricated. Results of experiments with the prototype brake are very encouraging and are in close agreement with the theoretical performance predictions.

scholarly journals Random adjustment - based Chaotic Metaheuristic algorithms for image contrast enhancement

2017 ◽  
Vol 10 (2) ◽  
pp. 67
Author(s):  
Vina Ayumi ◽  
L.M. Rasdi Rere ◽  
Mohamad Ivan Fanany ◽  
Aniati Murni Arymurthy
Keyword(s):  
Contrast Enhancement ◽  
Harmony Search ◽  
Search Space ◽  
Optimization Method ◽  
Large Solution ◽  
Swarm Optimization ◽  
Image Contrast Enhancement ◽  
Simulation Results ◽  
Better Than

Metaheuristic algorithm is a powerful optimization method, in which it can solve problemsby exploring the ordinarily large solution search space of these instances, that are believed tobe hard in general. However, the performances of these algorithms signicantly depend onthe setting of their parameter, while is not easy to set them accurately as well as completelyrelying on the problem's characteristic. To ne-tune the parameters automatically, manymethods have been proposed to address this challenge, including fuzzy logic, chaos, randomadjustment and others. All of these methods for many years have been developed indepen-dently for automatic setting of metaheuristic parameters, and integration of two or more ofthese methods has not yet much conducted. Thus, a method that provides advantage fromcombining chaos and random adjustment is proposed. Some popular metaheuristic algo-rithms are used to test the performance of the proposed method, i.e. simulated annealing,particle swarm optimization, dierential evolution, and harmony search. As a case study ofthis research is contrast enhancement for images of Cameraman, Lena, Boat and Rice. Ingeneral, the simulation results show that the proposed methods are better than the originalmetaheuristic, chaotic metaheuristic, and metaheuristic by random adjustment.

scholarly journals A two-stage evolutionary optimization approach for an irrigation system design

2016 ◽  
Vol 19 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Milan Cisty ◽  
Zbynek Bajtek ◽  
Lubomir Celar
Keyword(s):  
Water Distribution ◽  
Irrigation System ◽  
Optimal Solution ◽  
Water Distribution Network ◽  
Search Space ◽  
Optimization Method ◽  
Global Optimum ◽  
Optimization Approach ◽  
Nsga Ii ◽  
Irrigation Network

In this work, an optimal design of a water distribution network is proposed for large irrigation networks. The proposed approach is built upon an existing optimization method (NSGA-II), but the authors are proposing its effective application in a new two-step optimization process. The aim of the paper is to demonstrate that not only is the choice of method important for obtaining good optimization results, but also how that method is applied. The proposed methodology utilizes as its most important feature the ensemble approach, in which more optimization runs cooperate and are used together. The authors assume that the main problem in finding the optimal solution for a water distribution optimization problem is the very large size of the search space in which the optimal solution should be found. In the proposed method, a reduction of the search space is suggested, so the final solution is thus easier to find and offers greater guarantees of accuracy (closeness to the global optimum). The method has been successfully tested on a large benchmark irrigation network.

An improved aerodynamic performance optimization method of 3-D low Reynolds number rotor blade

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shuyi Zhang ◽  
Bo Yang
Keyword(s):  
Neural Network ◽  
Reynolds Number ◽  
Performance Optimization ◽  
Rotor Blade ◽  
Optimization Method ◽  
Aerodynamic Performance ◽  
Aerodynamic Optimization ◽  
Parametrization Method ◽  
Value Evaluation ◽  
Fitness Value

Abstract In this paper, an improved aerodynamic performance optimization method for 3-D low Reynolds number (Re) rotor blade is proposed. A conventional optimization procedure of blade is usually divided into three parts, such as the parameterization method, the fitness value evaluation and the optimization algorithm. This work is mainly focused on the first two parts. The parametrization method, Camber-FFD, is presented based on the camber parametrization method and the free-form deformation algorithm (FFD). The shape of 3-D blade is parameterized by the incidence angles and the coordinates of the maximum camber points. The fitness value evaluation has been realized with the help of an adaptive topological back propagation multi-layer forward artificial neural network (BP-MLFANN). During the training of BP-MLFANN, the hybrid particle swarm optimization method combined with the modified very fast simulate annealing algorithm (HPSO-MVFSA) is adopted to determine the neural network topology adaptively. To verify the effectiveness of this aerodynamic optimization method, the aerodynamic performance of a 3-D low-Re blade, such as Blade D900, is optimized, and the results are compared and analyzed based on the experiments and simulations. It is proved that this aerodynamic optimization method is feasible.

Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics

2010 ◽  
pp. 257-280
Author(s):  
Nicola Fanizzi ◽  
Claudia d’Amato ◽  
Floriana Esposito
Keyword(s):  
Distance Measure ◽  
Concept Drift ◽  
Fitness Function ◽  
Description Logics ◽  
Optimization Method ◽  
Optimal Choice ◽  
Validity Indices ◽  
Evolutionary Operators ◽  
Clustering Validity ◽  
The Given

We present a method based on clustering techniques to detect possible/probable novel concepts or concept drift in a Description Logics knowledge base. The method exploits a semi-distance measure defined for individuals, that is based on a finite number of dimensions corresponding to a committee of discriminating features (concept descriptions). A maximally discriminating group of features is obtained with a randomized optimization method. In the algorithm, the possible clusterings are represented as medoids (w.r.t. the given metric) of variable length. The number of clusters is not required as a parameter, the method is able to find an optimal choice by means of evolutionary operators and a proper fitness function. An experimentation proves the feasibility of our method and its effectiveness in terms of clustering validity indices. With a supervised learning phase, each cluster can be assigned with a refined or newly constructed intensional definition expressed in the adopted language.

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