Fejér monotonicity is a well-established property commonly observed in sequences generated by optimization algorithms. In this paper, we introduce an extension of this property, called Fejér* monotonicity, w...
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Asymptotic analysis of generic stochastic algorithms often relies on descent conditions. In a convex setting, some technical shortcuts can be considered to establish asymptotic convergence guarantees of the associated...
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The design optimization of synchronous reluctance (SyR) machines is considered in this paper by means of a Finite Element Analysis-based multi-objective optimization algorithm (MOOA). The research focuses on the desig...
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ISBN:
(纸本)9781479903375
The design optimization of synchronous reluctance (SyR) machines is considered in this paper by means of a Finite Element Analysis-based multi-objective optimization algorithm (MOOA). The research focuses on the design of the rotor geometry which is the key aspect of SyR machines design. In particular, this digest analyzes the performance of several popular MOOAs and the impact of their settings on the quality of the final design. A procedure to minimize the computational burden of the optimization process is introduced and applied for the first time to a five layer rotor. A rotor prototype has been realized to demonstrate the feasibility of the design procedure.
The aim of this paper is to present the relationship between complex networks and optimization algorithms. We investigate the genetic algorithms focus on the relationship of the individuals in each iteration and how t...
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ISBN:
(纸本)9781728131863
The aim of this paper is to present the relationship between complex networks and optimization algorithms. We investigate the genetic algorithms focus on the relationship of the individuals in each iteration and how the network emerge. The results are promising related to the complex networks properties and show that the Differential Evolution match with the small world networks. We model how the complex network connected component property seems to have relationship with fitness quality in the Imperialist competitive algorithm. Furthermore, we discuss how to improve optimization algorithm based on small networks.
In recent years, multimodal multiobjective optimization algorithms (MMOAs) based on evolutionary computation have been widely studied. However, existing MMOAs are mainly tested on benchmark function sets such as the 2...
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Aiming at the problem of noise filtering in the detection of industrial gear defects by machine vision technology, this paper makes some analysis and study for industrial gear image. For the analysis of denoising meth...
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Aiming at the problem of noise filtering in the detection of industrial gear defects by machine vision technology, this paper makes some analysis and study for industrial gear image. For the analysis of denoising method, it uses the method of MATLAB numerical simulation to apply single noise(like Gauss noise, salt and pepper noise, multiplicative noise) to gear image, and uses median filter, mean filter, Gaussian smoothing filter and Wiener filter separately to filtering and compare the different filtering effects. For the study of denoising fusion optimization, a neighborhood mean method based on extremum median filter and a fusion filter method are proposed for the mixed noise. The simulation results show that the median filtering is the best for salt and pepper noise, the smooth filtering and Wiener filtering are better for Gauss noise and multiplicative noise, and the fusion filtering method with improved mean filtering is the best for gear images with mixed noise.
Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a growing research topic with many competitive bio-inspired algorithms being proposed every year. In such an active area, prepar...
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This paper addresses the question of whether or not uncoupled online learning algorithms converge to the Nash equilibrium in pricing competition or whether they can learn to collude. Algorithmic collusion has been deb...
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The flexibility in protein docking is a major challenge in bioinformatic research. Protein docking problem is essentially an optimization problem. In this review we describe the methods of existing flexible protein-pr...
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The flexibility in protein docking is a major challenge in bioinformatic research. Protein docking problem is essentially an optimization problem. In this review we describe the methods of existing flexible protein-protein docking, focusing on the optimization algorithms. We divide the different methods into categories for presenting clearly.
In the current market economy, alliances play a key role in developing strategies across fields. In order to have a good partner, managers have used both qualitative and quantitative methodologies. This paper proposes...
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In the current market economy, alliances play a key role in developing strategies across fields. In order to have a good partner, managers have used both qualitative and quantitative methodologies. This paper proposes a mathematical model to figure out the most suitable strategic partners. With input data from published financial reports, the authors use the data envelopment analysis (DEA) to evaluate the business efficiency of the steel companies in the period of 2011-2019. Then, Grey system theory is applied to predict their performance in the future period. The findings recommend the two leading steel manufactures but having ineffective performance, the Hoa Sen Group, and the Pomina Steel Corporation, as the most feasible beneficial partnership. Managers and the government can take advantages of the model in order to implement and have overall plans of steel enterprise in the future.
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