A Framework of Multiobjective Collaborative Optimization

2009 ◽  
pp. 925-933 ◽  
Author(s):  
Haiyan Huang ◽  
Deyu Wang
Keyword(s):  
Collaborative Optimization

A Collaborative Optimization Approach for Multi-Train in URT

2020 ◽  
Author(s):  
Mo Chen ◽  
Pengfei Sun ◽  
Yu Rao ◽  
Yang Chai ◽  
Cheng Liu
Keyword(s):  
Collaborative Optimization ◽  
Optimization Approach

Collaborative optimization using response surface estimation

AIAA Journal ◽  
2000 ◽  
Vol 38 ◽  
pp. 1931-1938 ◽  
Author(s):  
I. P. Sobieski ◽  
I. M. Kroo
Keyword(s):  
Response Surface ◽  
Collaborative Optimization ◽  
Surface Estimation

Stereo superpixel: An iterative framework based on parallax consistency and collaborative optimization

2021 ◽  
Vol 556 ◽  
pp. 209-222
Author(s):  
Hua Li ◽  
Runmin Cong ◽  
Sam Kwong ◽  
Chuanbo Chen ◽  
Qianqian Xu ◽  
...  
Keyword(s):  
Collaborative Optimization ◽  
Iterative Framework

Support Vector Regression-Based Multidisciplinary Design Optimization for Ship Design

2012 ◽  
Author(s):  
Dongqin Li ◽  
Yifeng Guan ◽  
Qingfeng Wang ◽  
Zhitong Chen
Keyword(s):  
Design Optimization ◽  
Support Vector Regression ◽  
Design Process ◽  
Multidisciplinary Design Optimization ◽  
Initial Point ◽  
Ship Design ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Support Vector ◽  
Independent Design

The design of ship is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional design process of ship only involves independent design optimization within each discipline. With such an approach, there is no guarantee to achieve the optimum design. And at the same time improving the efficiency of ship optimization is also crucial for modem ship design. In this paper, an introduction of both the traditional ship design process and the fundamentals of Multidisciplinary Design Optimization (MDO) theory are presented and a comparison between the two methods is carried out. As one of the most frequently applied MDO methods, Collaborative Optimization (CO) promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, Design Of Experiment (DOE) and a new support vector regression algorithm are applied to CO to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method. Then this new Collaborative Optimization (CO) method using approximate technology is discussed in detail and applied in ship design which considers hydrostatic, propulsion, weight and volume, performance and cost. It indicates that CO method combined with approximate technology can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.

Metamodel-based robust collaborative optimization for the suspension parameters of rail vehicles

2019 ◽  
Vol 42 (8) ◽  
pp. 643-652
Author(s):  
Wenlong Liu ◽  
Yue Yang ◽  
Panpan Wang ◽  
Xiao Chen ◽  
Xiaobin Wei
Keyword(s):  
Collaborative Optimization ◽  
Suspension Parameters ◽  
Rail Vehicles

Study on Mix-Variable Collaborative Design Optimization

2012 ◽  
Vol 215-216 ◽  
pp. 592-596
Author(s):  
Li Gao ◽  
Rong Rong Wang
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimization Algorithm ◽  
Collaborative Design ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Collaborative Optimization ◽  
Continuous Variables ◽  
Complex Product ◽  
Divide And Rule

In order to deal with complex product design optimization problems with both discrete and continuous variables, mix-variable collaborative design optimization algorithm is put forward based on collaborative optimization, which is an efficient way to solve mix-variable design optimization problems. On the rule of “divide and rule”, the algorithm decouples the problem into some relatively simple subsystems. Then by using collaborative mechanism, the optimal solution is obtained. Finally, the result of a case shows the feasibility and effectiveness of the new algorithm.

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