Research in Multidisciplinary Collaborative Optimization Base on Symmetric Fuzzy Satisfaction

2012 ◽  
Vol 616-618 ◽  
pp. 2175-2181
Author(s):  
Nan Li ◽  
Bao Wei Song
Keyword(s):  
Optimization Algorithm ◽  
Optimization Design ◽  
System Optimization ◽  
Collaborative Optimization ◽  
System Level ◽  
Academic Level ◽  
Multi Level ◽  
The Impact

Multidisciplinary collaborative optimization (CO) is a multi-level optimization algorithm, which include system-level and academic level. Because these are many complications in Engineering, it will exist the fuzzy in Discipline-level optimization devices. If the impact of discipline-level ambiguity was ignored, it will lead to some big errors in the system optimization. In order to solve this problem, this paper introduced the optimal fuzzy satisfaction into multidisciplinary collaborative optimization design, and made it as optimal targets of sub-discipline optimization devices. Then a method of multidisciplinary collaborative optimization base on Fuzzy Satisfaction was get., which can solve the fuzzy problem in multidisciplinary collaborative optimization. Meanwhile this paper used this method in multidisciplinary collaborative optimization of torpedo, and compared the results that was get by this method with the results which was get by the method that did not base on the fuzzy satisfaction, finally get the conclusion that the method is fit to Multidisciplinary collaborative optimization of torpedo.

Multidisciplinary collaborative optimization based on relaxation method for solving complex problems

2020 ◽  
Vol 28 (4) ◽  
pp. 280-289
Author(s):  
Hamda Chagraoui ◽  
Mohamed Soula
Keyword(s):  
Optimization Problems ◽  
Inequality Constraints ◽  
Relaxation Method ◽  
Multidisciplinary Optimization ◽  
Collaborative Optimization ◽  
System Level ◽  
Dynamic Relaxation ◽  
Dynamic Relaxation Method ◽  
Feasible Solutions ◽  
The Impact

The purpose of the present work is to improve the performance of the standard collaborative optimization (CO) approach based on an existing dynamic relaxation method. This approach may be weakened by starting design points. First, a New Relaxation (NR) method is proposed to solve the difficulties in convergence and low accuracy of CO. The new method is based on the existing dynamic relaxation method and it is achieved by changing the system-level consistency equality constraints into relaxation inequality constraints. Then, a Modified Collaborative Optimization (MCO) approach is proposed to eliminate the impact of the information inconsistency between the system-level and the discipline-level on the feasibility of optimal solutions. In the MCO approach, the impact of the inconsistency is treated by transforming the discipline-level constrained optimization problems into an unconstrained optimization problem using an exact penalty function. Based on the NR method, the performance of the MCO approach carried out by solving two multidisciplinary optimization problems. The obtained results show that the MCO approach has improved the convergence of CO significantly. These results prove that the present MCO succeeds in getting feasible solutions while the CO fails to provide feasible solutions with the used starting design points.

Adaptive Collaborative Optimization Strategy Based on Genetic Algorithm

2011 ◽  
Vol 311-313 ◽  
pp. 32-36
Author(s):  
Ji Hong Liu ◽  
Hao Jiang ◽  
Qi Xie
Keyword(s):  
Genetic Algorithm ◽  
System Optimization ◽  
Collaborative Optimization ◽  
System Level ◽  
Optimization Strategy ◽  
Speed Reducer ◽  
Adaptive Penalty ◽  
Adaptive Penalty Function ◽  
Optimization Function ◽  
Definition Of

The genetic algorithm and the adaptive mechanism are adopted to tackle the inefficiency of optimization and the convergence difficulty of collaborative optimization (CO). Based on the further analysis of collaborative optimization process, the constraint conditions are converged into part of the optimization function. The system optimization model of CO has been reconstructed according to the adaptive penalty function which is based on the information of different disciplines and the transformation of system-level constraints. Therefore, the global and local search capabilities of optimization algorithm and searching efficiency of CO have been improved. Meanwhile, the difficulty of convergence caused by the internal definition of CO has been resolved. Finally, an example of speed reducer is demonstrated to verify the proposed method, showing that the convergence rate and search efficiency have been improved.

Fuzzy optimization design-based multi-level response surface of bogie frame

2019 ◽  
Vol 10 (2) ◽  
pp. 134-148 ◽  
Author(s):  
Pengpeng Zhi ◽  
Yonghua Li ◽  
Bingzhi Chen ◽  
Meng Li ◽  
Guannan Liu
Keyword(s):  
Boundary Conditions ◽  
Response Surface ◽  
Optimization Algorithm ◽  
Optimization Design ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Content Type ◽  
Design Variables ◽  
Multi Level ◽  
Response Surface Function

Purpose In a structural optimization design-based single-level response surface, the number of optimal variables is too much, which not only increases the number of experiment times, but also reduces the fitting accuracy of the response surface. In addition, the uncertainty of the optimal variables and their boundary conditions makes the optimal solution difficult to obtain. The purpose of this paper is to propose a method of fuzzy optimization design-based multi-level response surface to deal with the problem. Design/methodology/approach The main optimal variables are determined by Monte Carlo simulation, and are classified into four levels according to their sensitivity. The linear membership function and the optimal level cut set method are applied to deal with the uncertainties of optimal variables and their boundary conditions, as well as the non-fuzzy processing is carried out. Based on this, the response surface function of the first-level design variables is established based on the design of experiments. A combinatorial optimization algorithm is developed to compute the optimal solution of the response surface function and bring the optimal solution into the calculation of the next level response surface, and so on. The objective value of the fourth-level response surface is an optimal solution under the optimal design variables combination. Findings The results show that the proposed method is superior to the traditional method in computational efficiency and accuracy, and improves 50.7 and 5.3 percent, respectively. Originality/value Most of the previous work on optimization was based on single-level response surface and single optimization algorithm, without considering the uncertainty of design variables. There are very few studies which discuss the optimization efficiency and accuracy of multiple design variables. This research illustrates the importance of uncertainty factors and hierarchical surrogate models for multi-variable optimization design.

Collaborative Optimization Algorithm Based on the Penalty Function

2014 ◽  
Vol 538 ◽  
pp. 447-450
Author(s):  
Zhi Xia Jiang ◽  
Pin Chao Meng ◽  
Yan Zhong Li ◽  
Wei Shi Yin
Keyword(s):  
Penalty Function ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Collaborative Optimization ◽  
System Level ◽  
Feasible Region ◽  
Relaxation Factor ◽  
Algorithm Stability ◽  
Calculation Process ◽  
Relaxation Factors

The paper discusses the collaborative optimization problems with bounded. Based the penalty function the system-level optimization convert to a unconstraint programming. To the discipline-level optimization, the normalized weighted coefficients are used and combine relaxation factors to solve. It uses the relaxation factor to expand the feasible region, and possibly makes the iteration in the calculation process run inside feasible region. The data have shown that the algorithm has expanded the choice range of the initial points with high calculation accuracy and better algorithm stability.

Component-Oriented Decomposition for Collaborative Optimization in Reinforcement Concrete Bridge Design

2011 ◽  
Vol 374-377 ◽  
pp. 2405-2410
Author(s):  
Lian Fa Wang ◽  
Ai Ping Tang
Keyword(s):  
Optimization Design ◽  
Target Function ◽  
Inequality Constraints ◽  
Optimization Methods ◽  
Collaborative Optimization ◽  
System Level ◽  
Optimization Strategy ◽  
Bridge Design ◽  
Direct Construction ◽  
Consistency Constraints

In order to implement the bi-level optimization strategy-collaborative optimization (CO) to bridge design, bridge optimization design process is subdivided into three subsystems in terms of component-oriented decomposition: superstructure subsystem, bearing subsystem and substructure subsystem. For system level, target function is formulated with the total direct construction cost, and inequality constraints induced relaxation factors are adopted to relax the intersubsystem consistency constraints. For subsystems, target functions are formulated with discrepancy expressions and constraints are formulated according to corresponding codes demands respectively. The feasibility and validity of the proposed approach are examined with an optimization process of reinforcement concrete box girder bridge. Optimization results from proposed approach are compared with that from mono-discipline optimization. The proposed approach shows high computing efficiency than mono-discipline optimization methods when achieving same optimization results.

On the Impact of Coupling Strength on Complex System Optimization for Single-Level Formulations

2005 ◽  
Author(s):  
James Allison ◽  
Michael Kokkolaras ◽  
Panos Papalambros
Keyword(s):  
Complex System ◽  
Decision Making ◽  
Coupling Strength ◽  
System Optimization ◽  
Solution Strategy ◽  
Single Level ◽  
Complexity Management ◽  
Modern Engineering ◽  
Multi Level ◽  
The Impact

Design of modern engineering products requires complexity management. Several methodologies for complex system optimization have been developed in response. Single-level strategies centralize decision-making authority, while multi-level strategies distribute the decision-making process. This article studies the impact of coupling strength on single-level Multidisciplinary Design Optimization formulations, particularly the Multidisciplinary Feasible (MDF) and Individual Disciplinary Feasible (IDF) formulations. The Fixed Point Iteration solution strategy is used to motivate the analysis. A new example problem with variable coupling strength is introduced, involving the design of a turbine blade and a fully analytic mathematical model. The example facilitates a clear illustration of MDF and IDF and provides an insightful comparison between these two formulations. Specifically, it is shown that MDF is sensitive to variations in coupling strength, while IDF is not.

Comparative assessment of morphological mechanisms of maintaining structural liver homeostasis in the dynamics of exposure to coal-rock dust and sodium fluoride on the body

2020 ◽  
pp. 189-194
Author(s):  
M. S. Bugaeva ◽  
O. I. Bondarev ◽  
N. N. Mikhailova ◽  
L. G. Gorokhova
Keyword(s):  
Sodium Fluoride ◽  
Morphological Changes ◽  
The Body ◽  
System Level ◽  
Production Factor ◽  
Coal Rock ◽  
The Impact ◽  
Structural Homeostasis ◽  
Rock Dust

Introduction. The impact on the body of such factors of the production environment as coal-rock dust and fluorine compounds leads to certain shift s in strict indicators of homeostasis at the system level. Maintaining the relative constancy of the internal environment of the body is provided by the functional consistency of all organs and systems, the leading of which is the liver. Organ repair plays a crucial role in restoring the structure of genetic material and maintaining normal cell viability. When this mechanism is damaged, the compensatory capabilities of the organ are disrupted, homeostasis is disrupted at the cellular and organizational levels, and the development of the main pathological processes is noted.The aim of the study is to compare the morphological mechanisms of maintaining structural homeostasis of the liver in the dynamics of the impact on the body of coal-rock dust and sodium fluoride.Materials and methods. Experimental studies were conducted on adult white male laboratory rats. Features of morphological mechanisms for maintaining structural homeostasis of the liver in the dynamics of exposure to coal-rock dust and sodium fluoride were studied on experimental models of pneumoconiosis and fluoride intoxication. For histological examination in experimental animals, liver sampling was performed after 1, 3, 6, 9, 12 weeks of the experiment.Results. The specificity of morphological changes in the liver depending on the harmful production factor was revealed. It is shown that chronic exposure to coal-rock dust and sodium fluoride is characterized by the development of similar morphological changes in the liver and its vessels from the predominance of the initial compensatory-adaptive to pronounced violations of the stromal and parenchymal components. Long-term inhalation of coal-rock dust at 1–3 weeks of seeding triggers adaptive mechanisms in the liver in the form of increased functional activity of cells, formation of double-core hepatocytes, activation of immunocompetent cells and endotheliocytes, ensuring the preservation of the parenchyma and the general morphostructure of the organ until the 12th week of the experiment. Exposure to sodium fluoride leads to early disruption of liver compensatory mechanisms and the development of dystrophic changes in the parenchyma with the formation of necrosis foci as early as the 6th week of the experiment.Conclusions. The study of mechanisms for compensating the liver structure in conditions of long-term exposure to coal-rock dust and sodium fluoride, as well as processes that indicate their failure, and the timing of their occurrence, is of theoretical and practical importance for developing recommendations for the timely prevention and correction of pathological conditions developing in employees of the aluminum and coal industry.The authors declare no conflict of interests.

Multi-level Barriers for Utilization of Youth Friendly Reproductive Health Services (YFRHS) among Youths

2020 ◽  
Vol 8 ◽  
pp. 95-108
Author(s):  
Shanti Prasad Khanal
Keyword(s):  
Reproductive Health ◽  
Health Services ◽  
Health System ◽  
System Level ◽  
Mixed Method Research ◽  
Reproductive Health Services ◽  
Group Discussions ◽  
Personal Level ◽  
Multi Level ◽  
Youth Friendly

 The present study aims to examine the multi-level barriers to utilize by the youth-friendly reproductive health services (YFRHS) among the school-going youths of the Surkhet valley of Nepal. This study is based on the sequential explanatory research design under mixed-method research. The quantitative data were collected using the self- administered questionnaire from the 249 youths, aged between the 15-24 years, those selected by using random sampling. The qualitative data were collected using the Focus Group Discussions (FGDs) from the 12 participants who were selected purposively. The study confirmed that school-going youths do not have appropriate utilization of YFHS due to multi-layered barriers. However, the utilization of the service was higher among females, those the older age group, studying in the upper classes, the upper castes, and married youths. The key findings and themes are recognized as multi-layered barriers including personal-level, health system-level, community-level, and policy-level on the entire socio-ecological field. Among them, the existing health system is the foremost barrier. Multi-level interventions are, therefore, required to increase the YFRHS utilization and improve concerns for school-going-youths.  

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