The Multi-Objective Optimization under Random Loads

2012 ◽  
Vol 166-169 ◽  
pp. 548-552
Author(s):  
Xian Jie Wang ◽  
Xun An Zhang ◽  
Yeda Lian
Keyword(s):  
High Performance ◽  
Low Cost ◽  
Structure Optimization ◽  
Extreme Value Distribution ◽  
Random Excitation ◽  
Probability Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Structure Reliability ◽  
Random Loads

Structure optimization seeks to achieve the best performance for a structure while satisfying various constrains such as a given probability. In the traditional mathematical model of structure optimization, the goal and the restraint functions are given without considering the randomness of the structural system. In this paper, the random loads and strength are described by probability method, the structure reliability is considered as objective function. Using the genetic algorithm, the mega-sub controlled structural systems is multi-objective optimization designed based on the structure reliability under random excitation, combined with the probability density evolution method for evaluation of extreme value distribution. A low-cost and high-performance structure is getting.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

scholarly journals Correction: A multi-objective optimization-based layer-by-layer blade-coating approach for organic solar cells: rational control of vertical stratification for high performance

2020 ◽  
Vol 13 (1) ◽  
pp. 317-317
Author(s):  
Rui Sun ◽  
Jie Guo ◽  
Qiang Wu ◽  
Zhuohan Zhang ◽  
Wenyan Yang ◽  
...  
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
High Performance ◽  
Vertical Stratification ◽  
Layer By Layer ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Rational Control ◽  
Blade Coating ◽  
Energy Environ

Correction for ‘A multi-objective optimization-based layer-by-layer blade-coating approach for organic solar cells: rational control of vertical stratification for high performance’ by Rui Sun et al., Energy Environ. Sci., 2019, 12, 3118–3132.

scholarly journals Energy Saving and Low-Cost-Oriented Design Processes of Blank’s Dimensions Based on Multi-Objective Optimization Model

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 811 ◽  
Author(s):  
Yongmao Xiao ◽  
Qingshan Gong ◽  
Xiaowu Chen
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Optimization Model ◽  
Low Cost ◽  
Minimum Cost ◽  
Processing Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Set Up

The blank’s dimensions are an important focus of blank design as they largely determine the energy consumption and cost of manufacturing and further processing the blank. To achieve energy saving and low cost during the optimization of blank dimensions design, we established energy consumption and cost objectives in the manufacturing and further processing of blanks by optimizing the parameters. As objectives, we selected the blank’s production and further processing parameters as optimization variables to minimize energy consumption and cost, then set up a multi-objective optimization model. The optimal blank dimension was back calculated using the parameters of the minimum processing energy consumption and minimum cost state, and the model was optimized using the non-dominated genetic algorithm-II (NSGA-II). The effect of designing blank dimension in saving energy and costs is obvious compared with the existing methods.

Use of nonlinear asymmetrical shock absorbers in multi-objective optimization of the suspension system in a variety of road excitations

2016 ◽  
Vol 231 (2) ◽  
pp. 372-387 ◽  
Author(s):  
Abolfazl Seifi ◽  
Reza Hassannejad ◽  
Mohammad Ali Hamed
Keyword(s):  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Low Cost ◽  
Suspension System ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Vehicle Handling ◽  
Multi Objective ◽  
Shock Absorbers ◽  
The Impact

In this study, a new method to improve ride comfort, vehicle handling, and workspace was presented in multi-objective optimization using nonlinear asymmetrical dampers. The main aim of this research was to provide suitable passive suspension based on more efficiency and the low cost of the mentioned dampers. Using the model with five degrees of freedom, suspension system parameters were optimized under sinusoidal road excitation. The main functions of the suspension system were chosen as objective functions. In order to better illustrate the impact of each objective functions on the suspension parameters, at first two-objective and finally five-objective were considered in the optimization problem. The obtained results indicated that the optimized viscous coefficients for five-objective optimization lead to 3.58% increase in ride comfort, 0.74% in vehicle handling ability, and 2.20% in workspace changes for the average of forward and rear suspension.

scholarly journals Low-Cost Multi-Objective Optimization of Multiparameter Antenna Structures Based on the l1 Optimization BPNN Surrogate Model

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 839
Author(s):  
Dong ◽  
Qin ◽  
Mo
Keyword(s):  
Surrogate Model ◽  
Communication Systems ◽  
Low Cost ◽  
Computational Cost ◽  
Optimization Method ◽  
Antenna Design ◽  
Multi Objective Optimization ◽  
Compact Structure ◽  
Multi Objective ◽  
L1 Optimization

The development of modern wireless communication systems not only requires the antenna to be lightweight, low cost, easy to manufacture and easy to integrate but also imposes requirements on the miniaturization, wideband, and multiband design of the antenna. Therefore, designing an antenna that quickly and effectively meets multiple performance requirements is of great significance. To solve the problem of the large computational cost of traditional multi-objective antenna design methods, this paper proposes a backpropagation neural network surrogate model based on l1 optimization (l1-BPNN). The l1 optimization method tends to punish larger weight values and select smaller weight values so as to preserve a small amount of important weights and reset relatively unimportant weights to zero. By using l1 optimization method, the network mapping structure can be automatically adjusted to achieve the most suitable and compact structure of the surrogate model. Furthermore, for multi-parameter antenna design problems, a fast multi-objective optimization framework is constructed using the proposed l1-BPNN as a surrogate model. The framework is illustrated using a miniaturized multiband antenna design case, and a comparison with previously published methods, as well as numerical validation, is also provided.

scholarly journals SOM-Based High-Dimensional Design Spaces Mapping for Multi-Objective Optimization

2020 ◽  
Vol 38 (3) ◽  
pp. 677-684
Author(s):  
Zebin Zhang ◽  
Pengfei Zhang ◽  
Ruizhen Li
Keyword(s):  
Design Method ◽  
Low Cost ◽  
Data Extraction ◽  
Load Ratio ◽  
Design Parameters ◽  
High Dimensional ◽  
Multi Objective Optimization ◽  
Pocket Depth ◽  
Sliding Bearing ◽  
Multi Objective

Multi-objective optimization can reveal the complex parameter-objective relationships in the high-dimensional design problems. However, the data-extraction and data-presentation of the high-dimensional complex nonlinear system suffers from the increasing dimensionality. Key features and data-distribution of high-dimensional design spaces:parameter and objective spaces could be obtained by using Self-Organizing Maps (SOM) method, which re-clusters the high-dimensional multi-attribute data existing on the Pareto front into several low-dimensional maps. Correlations among all the design variables can be drawn according the colorized topological structure of the maps. Under the constraints including geometric structure and operating parameters, a low-cost and high accurate Kriging surrogate model was established to optimize a hybrid sliding bearing based on the sequential design method. Correlations between 3 objectives:"friction-to-load" ratio, temperature rise, instability threshold speed and 4 design parameters were extracted by SOM. Optimal feature regions were captured and analyzed. Results show that, within the specific feasible design space, supply pressure, axial bearing land width have important impact on the selected objectives, whereas the other parameters such as deep pocket depth and shallow pocket angle have relatively limited impact. A series of corresponding design decisions and optimization results help to understand the mechanism of the hybrid sliding bearing system in a much more intuitive way.

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