scholarly journals Multi-Variable Multi-Objective Optimization Algorithm for Optimal Design of PMa-SynRM for Electric Bicycle Traction Motor

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1901
Author(s):  
Ji-Chang Son ◽  
Kyung-Pyo Yi ◽  
Dong-Kuk Lim
Keyword(s):  
Optimal Design ◽  
Optimization Method ◽  
Pattern Search ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Multi Objective ◽  
Weighted Sum Method ◽  
Function Calls ◽  
Electric Bicycle ◽  
Conventional Optimization

In this paper, internal division point genetic algorithm (IDP-GA) was proposed to lessen the computational burden of multi-variable multi-objective optimization problem using finite element analysis such as optimal design of electric bicycles. The IDP-GA could consider various objectives with normalized weighted sum method and could reduce the number of function calls with novel crossover strategy and vector-based pattern search method. The superiority of the proposed algorithm was verified by comparing performances with conventional optimization method at two mathematical test functions. Finally, the applicability of the IDP-GA in practical electric machine design was verified by successfully deriving an improved design of electric bicycle propulsion motor.

scholarly journals Problems of a Utopia Point Setting in Transformation of Individual Objective Functions in Multi-Objective Optimization

2019 ◽  
Vol 27 (45) ◽  
pp. 64-71
Author(s):  
Pavel Važan ◽  
Zuzana Červeňanská ◽  
Janette Kotianová ◽  
Jiří Holík
Keyword(s):  
Production Control ◽  
A Priori ◽  
Optimization Method ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Weighted Sum Method ◽  
The Individual ◽  
Utopia Point

Abstract In an optimal processes control, where the considered goals are in general observed as concurrently conflicted, a multi-objective approach fits the best. Commonly used scalarization techniques in multi-objective optimization need a transformation of the individual single-objective functions involved into a scalar multi-criteria objective function. There are many parameters which can influence the optimization results solutions, including an unreachable utopia point value. In this study, the authors compare the multi-objective problem solutions found via two ways of the individual objectives transformation with the respect to setting the utopia point. The methods are used in the area of production control in a case study for a batch production system. To find the solutions, The Weighted Sum Method with a priori articulated preferences under specific constraints as the scalar multi-objective optimization method is applied in simulation optimization.

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.

Belt width optimization for tire durability enhancement

2021 ◽  
pp. 095440702110352
Author(s):  
Li Hongling ◽  
Dong Yude ◽  
Qiu Lei ◽  
Sun Juxin
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Durability Test ◽  
Element Analysis ◽  
Multi Objective ◽  
Analysis Technique ◽  
Mechanical Products ◽  
Belt Width

Tire burst is one of the hot issues in automobile market. Based on the tire burst problem of all-steel radial tire, the shear strain and strain energy density at the end of the belt layer are analyzed to extend the tire durability. A multi-objective optimization model was established by finite element analysis, and the function constraints conditions were set. The optimization scheme was determined using differential evolution (DE) method. The finite element simulation and the durability test of tire specimen show that tire performance has greatly improved after the optimization. The results show that the combination of the finite element analysis technique and the multi-objective optimization method can effectively reduce a lot of labor, material, and financial resources in the structural optimization of mechanical products.

Multi-Objective Optimization Algorithm for Instrument Integrated Development

2010 ◽  
Vol 44-47 ◽  
pp. 3487-3491
Author(s):  
Guo Xin Wu ◽  
Xiao Li Xu
Keyword(s):  
Optimal Design ◽  
Optimization Algorithm ◽  
Collaborative Design ◽  
Optimal Solution ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Integrated Development ◽  
Multi Objective ◽  
Individual Fitness ◽  
The Individual

The integrated technology is the main way for the instrument development. The combination of networked collaborative design and multi-objective optimization method, considering the different product design and development of individual fitness degree, to provide the best integrated development for the product solution. The system of Flexible integrated knowledge management was built for networked collaborative design. The system architecture is flexible hub, to support the collaborative development of decision-making and optimal design of innovative integrated development. Innovative multi-objective optimization algorithm also was established based on networked collaborative design. It is realized to obtain fast convergence of the optimal solution set for Knowledge groups. The individual goals, to achieve the optimal design of integrated development, were achieved.

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.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

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