Increasing Output in Transfer Lines through Adaptive Buffer Operation

2016 ◽  
Author(s):  
Jeanette Hamiga
Keyword(s):  
Production System ◽  
Optimization Problem ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Labor Costs ◽  
Serial Transfer ◽  
Transfer Lines ◽  
Multi Objective ◽  
Simulation Based ◽  
Decoupling Effect

This thesis is intended for engineers and scientists in the field of production. It deals with the goal of increasing output in (serial) transfer lines and simultaneously decreasing labor costs without need of change to the structure of the production system. For this the method adaptive buffer operation is developed, implemented and validated. Adaptive buffer operation proposes a different way of operating buffers, improving the decoupling effect of buffers. The buffers are filled to certain target fill levels at fixed moments (times of the day). Apart from the target fill levels further parameters, e.g. moments of intervention or the intervention frequency, are identified. To find out how to operate the buffers and which parameter combinations work best, a simulation-based optimization method is proposed. This method is split into the evaluative ­methodology, here simulation, and the generative technique of evolution strategies, solving the multi-objective optimization problem. Proo...

scholarly journals Multi-objective Optimization of Compliant Parallel Platform for Desired Stiffness and Workspace

2021 ◽  
Author(s):  
Hongwei Xu ◽  
Haibo Zhou ◽  
Zhiqiang Li ◽  
Xia Ju
Keyword(s):  
Numerical Model ◽  
Optimization Problem ◽  
Structural Parameters ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Multi Objective ◽  
Performance Indexes ◽  
Parallel Platform ◽  
The Relationship

Abstract Stiffness and workspace are crucial performance indexes of a precision mechanism. In this paper, an optimization method is presented, for a compliant parallel platform to achieve desired stiffness and workspace. First, a numerical model is proposed to reveal the relationship between structural parameters, desired stiffness and workspace of the compliant parallel platform. Then, the influence of the various parameters on stiffness and workspace of the platform is analyzed. Based on Gaussian distribution, the multi-objective optimization problem is transformed into a single-objective one, in order to guarantee convergence precision. Furthermore, particle swarm optimization is used to optimize the structural parameters of the platform, which significantly improve its stiffness and workspace. Last, the effectiveness of the proposed numerical model is verified by finite element analysis and experiment.

scholarly journals Multi-Objective Optimization of the Gate Driver Parameters in a SiC-Based DC-DC Converter for Electric Vehicles

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3720
Author(s):  
Milad Moradpour ◽  
Paolo Pirino ◽  
Michele Losito ◽  
Wulf-Toke Franke ◽  
Amit Kumar ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Electromagnetic Interference ◽  
Optimization Problem ◽  
Experimental Tests ◽  
Wide Band ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gate Driver ◽  
Efficient Power

DC-DC converters are being used for power management and battery charging in electric vehicles (EVs). To further the role of EVs in the market, more efficient power electronic converters are needed. Wide band gap (WBG) devices such as silicon carbide (SiC) provide higher frequency and lower power loss, however, their high di/dt and dv/dt transients result in higher electromagnetic interference (EMI). On the other hand, some gate driver parameters such as gate resistor ( R G ) have a contradictory effect on efficiency ( η ) and EMI. The idea of this paper is to investigate the values of these parameters using a multi-objective optimization method to optimize η and EMI at the same time. To this aim, first, the effect of high and low side R G on η and EMI in the half-bridge configuration is studied. Then, the objective functions of the optimization problem are obtained using a numerical regression method on the basis of the experimental tests. Then, the values of the gate resistors are obtained by solving the multi-objective optimization problem. Finally, η and EMI of the converter in the optimum gate resistor design are compared to those in the conventional design to validate the effectiveness of the proposed design approach.

scholarly journals Identification of Essential Proteins using a Novel Multi-objective Optimization Method

2020 ◽  
Author(s):  
Chong Wu ◽  
Houwang Zhang ◽  
Le Zhang ◽  
Hanying Zheng
Keyword(s):  
Protein Interactions ◽  
Optimization Problem ◽  
State Of The Art ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Protein Protein Interactions ◽  
Generalization Ability ◽  
Essential Proteins ◽  
Multi Objective ◽  
Voting Strategy

<p>Using graph theory to identify essential proteins is a hot topic at present. These methods are called network-based methods. However, the generalization ability of most network-based methods is not satisfactory. Hence, in this paper, we consider the identification of essential proteins as a multi-objective optimization problem and use a novel multi-objective optimization method to solve it. The optimization result is a set of Pareto solutions. Every solution in this set is a vector which has a certain number of essential protein candidates and is considered as an independent predictor or voter. We use a voting strategy to assemble the results of these predictors. To validate our method, we apply it on the protein-protein interactions (PPI) datasets of two species (Yeast and Escherichia coli). The experiment results show that our method outperforms state-of-the-art methods in terms of sensitive, specificity, F-measure, accuracy, and generalization ability.</p>

scholarly journals Identification of Essential Proteins using a Novel Multi-objective Optimization Method

2020 ◽  
Author(s):  
Chong Wu ◽  
Houwang Zhang ◽  
Le Zhang ◽  
Hanying Zheng
Keyword(s):  
Protein Interactions ◽  
Optimization Problem ◽  
State Of The Art ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Protein Protein Interactions ◽  
Generalization Ability ◽  
Essential Proteins ◽  
Multi Objective ◽  
Voting Strategy

<p>Using graph theory to identify essential proteins is a hot topic at present. These methods are called network-based methods. However, the generalization ability of most network-based methods is not satisfactory. Hence, in this paper, we consider the identification of essential proteins as a multi-objective optimization problem and use a novel multi-objective optimization method to solve it. The optimization result is a set of Pareto solutions. Every solution in this set is a vector which has a certain number of essential protein candidates and is considered as an independent predictor or voter. We use a voting strategy to assemble the results of these predictors. To validate our method, we apply it on the protein-protein interactions (PPI) datasets of two species (Yeast and Escherichia coli). The experiment results show that our method outperforms state-of-the-art methods in terms of sensitive, specificity, F-measure, accuracy, and generalization ability.</p>

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

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