scholarly journals Research and Application on a Novel Clustering Algorithm of Quantum Optimization in Server Load Balancing

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Dong Yumin ◽  
Xiao Shufen ◽  
Jia Fanghua ◽  
Li Jinhai
Keyword(s):  
Clustering Algorithm ◽  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Optimization Scheme ◽  
Analog Simulation ◽  
Energy Field ◽  
Network Cluster ◽  
Simulation And Experiment ◽  
Annealing Algorithm ◽  
Quantum Optimization

A quantum optimization scheme in network cluster server task scheduling is proposed. We explore and research the distribution theory of energy field in quantum mechanics; specially, we apply it to data clustering. We compare the quantum optimization method with genetic algorithm (GA), ant colony optimization (ACO), simulated annealing algorithm (SAA). At the same time, we prove its validity and rationality by analog simulation and experiment.

Parameter Design of Conformal PML Based on 2D Monostatic RCS Optimization

2021 ◽  
Vol 36 (6) ◽  
pp. 726-733
Author(s):  
Yongjie Zhang ◽  
Xiaofeng Deng
Keyword(s):  
Electromagnetic Scattering ◽  
Simulated Annealing Algorithm ◽  
Design Method ◽  
Optimization Method ◽  
Parameter Design ◽  
Design Parameters ◽  
Absorption Effect ◽  
Absorbing Boundary ◽  
Design And Optimization ◽  
Annealing Algorithm

In this study, 2D finite element (FE) solving process with the conformal perfectly matched layer (PML) is elucidated to perform the electromagnetic scattering computation. With the 2D monostatic RCS as the optimization objective, a sensitivity analysis of the basic design parameters of conformal PML (e.g., layer thickness, loss factor, extension order and layer number) is conducted to identify the major parameters of conformal PML that exerts more significant influence on 2D RCS. Lastly, the major design parameters of conformal PML are optimized by the simulated annealing algorithm (SA). As revealed from the numerical examples, the parameter design and optimization method of conformal PML based on SA is capable of enhancing the absorption effect exerted by the conformal PML and decreasing the error of the RCS calculation. It is anticipated that the parameter design method of conformal PML based on RCS optimization can be applied to the cognate absorbing boundary and 3D electromagnetic computation.

A New Kind of Optimization Method for Gear Design

2012 ◽  
Vol 190-191 ◽  
pp. 7-10 ◽  
Author(s):  
Yu Guo Wu
Keyword(s):  
Simulated Annealing Algorithm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Bp Algorithm ◽  
Mean Square ◽  
Test Results ◽  
Swarm Optimization ◽  
Design Efficiency ◽  
Gear Design ◽  
Annealing Algorithm

In order to raise the design efficiency and get the most excellent design effect, this paper combined Particle Swarm Optimization (PSO) algorithm and put forward a new kind of neural network, based on PSO algorithm and NARMA model. It gives the basic theory, steps and algorithm; The test results show that rapid global convergence and reached the lesser mean square error MSE) when compared with Genetic Algorithm, Simulated Annealing Algorithm, the BP algorithm with momentum term.

Free Parameter Optimization of DTMDs Based on Improved Hybrid Genetic-Simulated Annealing Algorithm

2020 ◽  
Vol 20 (03) ◽  
pp. 2050031
Author(s):  
Qiang Han ◽  
Xuan Zhang ◽  
Kun Xu ◽  
Xiuli Du
Keyword(s):  
Simulated Annealing ◽  
Parameter Optimization ◽  
Free Parameter ◽  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Design Parameters ◽  
Mass Ratio ◽  
Tuned Mass Dampers ◽  
Genetic Simulated Annealing Algorithm ◽  
Annealing Algorithm

The optimum design of distributed tuned mass dampers (DTMDs) is normally based on predefined restrictions, such as the location and/or mass ratio of the tuned mass dampers (TMDs). To further improve the control performance, a free parameter optimization method (FPOM) is proposed. This method only restricts the total mass of the DTMDs system and takes the installation position, mass ratio, stiffness and damping of each TMD as parameters to be optimized. An improved hybrid genetic-simulated annealing algorithm (IHGSA) is adopted to find the optimum values of the design parameters. This algorithm can solve the non-convexity and multimodality problems of the objective function and is quite effective in dealing with the large amount of computations in the free parameter optimization. A numerical benchmark model is adopted to compare the control efficiency of FPOM with conventional control scenarios, such as single TMD, multiple TMDs and DTMDs optimized through conventional methods. The results show that the DTMDs system optimized by using FPOM is superior to the other control scenarios for the same value of mass ratio.

scholarly journals A Stone Resource Assignment Model under the Fuzzy Environment

2012 ◽  
Vol 2012 ◽  
pp. 1-26 ◽  
Author(s):  
Liming Yao ◽  
Jiuping Xu ◽  
Feng Guo
Keyword(s):  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Resource Assignment ◽  
Possibility Measure ◽  
Fuzzy Environment ◽  
Assignment Model ◽  
Simulation Based ◽  
Annealing Algorithm ◽  
Upper Level

This paper proposes a bilevel multiobjective optimization model with fuzzy coefficients to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone plant so as to minimize total emissions and maximize employment and economic profit. On the lower level, stone plants must reasonably assign stone resources to produce different stone products under the exploitation constraint. To deal with inherent uncertainties, the object functions and constraints are defuzzified using a possibility measure. A fuzzy simulation-based improved simulated annealing algorithm (FS-ISA) is designed to search for the Pareto optimal solutions. Finally, a case study is presented to demonstrate the practicality and efficiency of the model. Results and a comparison analysis are presented to highlight the performance of the optimization method, which proves to be very efficient compared with other algorithms.

The Application and Comparison of Two Different Optimization Algorithms in the Optimization Design of Hydrofoil

2012 ◽  
Vol 178-181 ◽  
pp. 2871-2876
Author(s):  
Chao Wang ◽  
Feng Feng ◽  
Xin Chang ◽  
Chun Yu Guo ◽  
Yang Hao Liu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Design ◽  
Simulated Annealing Algorithm ◽  
Optimization Algorithms ◽  
Optimization Method ◽  
Flow Solver ◽  
Propeller Design ◽  
Section Design ◽  
Annealing Algorithm

Hydrofoil is the important part of ship design and diverse motion equipment. The optimization design of hydrofoil section on lift-to-drag radio with genetic algorithm (GA) and simulated annealing algorithm are demonstrated, and the method on the hydrofoil section design of the propeller design will be done. Objective function and fitness of every individual are provided by flow solver of panel method. The optimization method on design of hydrofoil section on lift-to-drag is successfully used. The optimization results show the combination of optimization algorithm is feasible at the optimal design of hydrofoil sections. What’s more, a comparison between two different optimization algorithms is made, a conclusion that the simulated annealing algorithm is better then the genetic algorithm is obtained.

Structure Optimization of the Housing Fillet Using SA Combined with FEM

2014 ◽  
Vol 898 ◽  
pp. 217-220
Author(s):  
Jin Hong Ma ◽  
Bin Tao ◽  
Xiao Han Yao
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Simulated Annealing Algorithm ◽  
Structure Optimization ◽  
Optimization Method ◽  
Zero Order ◽  
Optimal Method ◽  
First Order ◽  
Universal Mill ◽  
Annealing Algorithm

The housing fillet of universal mill affects the strengthen and stiffness of mill. It is necessary to optimize the housing fillet. In this paper, the simulated annealing algorithm (SA) combined with finite element method (FEM) , a new kind of structural optimization method is established. MATLAB language is used to compile the program combined the SA with FEM to optimize housing fillet of universal mill. Compared with the zero order and first order optimization method of ANSYS program, the result of this optimal method is better.

Research on Optimal Deployment of HWSN Node Cost Based on Simulated Annealing Algorithm

2014 ◽  
Vol 651-653 ◽  
pp. 1921-1924
Author(s):  
Ji Tao Shen ◽  
Jun Yang Zhang
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Fault Tolerant ◽  
Monitoring Network ◽  
Optimization Method ◽  
Perception Model ◽  
Annealing Algorithm ◽  
Target Monitoring ◽  
The Cost ◽  
Network Fault Tolerance

An optimal heterogeneous sensor differentiated deployment schemes based on simulated annealing algorithm is proposed to solve the problems of the high density of distributing heterogeneity nodes in WSN and geographical irregularity of the sensed event. This method can not only apply to Boolean perception model of the node, but also apply to perception model. The algorithm uses the cost of sensors deployment as objective function in the context of assuring the coverage and fault tolerant of networks. The simulation results show that, the optimization method proposed in this paper can effectively convergence, under the premise to ensure network fault tolerance and robustness, reduces the cost of network deployment, improve the quality of target monitoring network.

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