Compact implementation of non-hierarchical analytical target cascading for coordinating distributed multidisciplinary design optimization problems

2017 ◽  
Vol 56 (6) ◽  
pp. 1597-1602 ◽  
Author(s):  
Bastien Talgorn ◽  
Michael Kokkolaras
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Problems ◽  
Multidisciplinary Design ◽  
Analytical Target Cascading ◽  
Target Cascading

scholarly journals An Enhanced Analytical Target Cascading and Kriging Model Combined Approach for Multidisciplinary Design Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ping Jiang ◽  
Jianzhuang Wang ◽  
Qi Zhou ◽  
Xiaolin Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Kriging Model ◽  
Multidisciplinary Design ◽  
High Approximation ◽  
Engineering Systems ◽  
Analytical Target Cascading ◽  
Combined Approach ◽  
Coordination Strategy ◽  
Target Cascading

Multidisciplinary design optimization (MDO) has been applied widely in the design of complex engineering systems. To ease MDO problems, analytical target cascading (ATC) organizes MDO process into multilevels according to the components of engineering systems, which provides a promising way to deal with MDO problems. ATC adopts a coordination strategy to coordinate the couplings between two adjacent levels in the design optimization process; however, existing coordination strategies in ATC face the obstacles of complicated coordination process and heavy computation cost. In order to conquer this problem, a quadratic exterior penalty function (QEPF) based ATC (QEPF-ATC) approach is proposed, where QEPF is adopted as the coordination strategy. Moreover, approximate models are adopted widely to replace the expensive simulation models in MDO; a QEPF-ATC and Kriging model combined approach is further proposed to deal with MDO problems, owing to the comprehensive performance, high approximation accuracy, and robustness of Kriging model. Finally, the geometric programming and reducer design cases are given to validate the applicability and efficiency of the proposed approach.

Multidisciplinary Optimization of Autonomous Rendezvous Spacecraft Using Updated Analytical Target Cascading Method

2012 ◽  
Vol 195-196 ◽  
pp. 801-806
Author(s):  
Bei Bei Wu ◽  
Hai Huang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Multidisciplinary Optimization ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Analytical Target Cascading ◽  
Analysis Model ◽  
Autonomous Rendezvous ◽  
Target Cascading ◽  
Practical Engineering

For the multidisciplinary design optimization (MDO) question of autonomous rendezvous spacecraft, first, the analysis model and coupling relations of payload, propulsion and structure discipline are discussed; then the updated analytical target cascading (UATC) method is introduced and compared with the widely used collaborative optimization (CO). Results prove that the UATC method requires 54.8% fewer average subspace iterations than the CO and is more efficient for practical engineering MDO problem. Finally, based on the UATC method, a MDO problem of autonomous rendezvous spacecraft is solved and gets reasonable and effective results. The process proves the effectiveness of UATC method solving spacecraft MDO problem.

Multi-objective collaborative multidisciplinary design optimization using particle swarm techniques and fuzzy decision making

2012 ◽  
Vol 226 (9) ◽  
pp. 2281-2295 ◽  
Author(s):  
Mohammad Reza Farmani ◽  
Jafar Roshanian ◽  
Meisam Babaie ◽  
Parviz M Zadeh
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Fuzzy Decision ◽  
Swarm Optimization ◽  
Multi Objective

This article focuses on the efficient multi-objective particle swarm optimization algorithm to solve multidisciplinary design optimization problems. The objective is to extend the formulation of collaborative optimization which has been widely used to solve single-objective optimization problems. To examine the proposed structure, racecar design problem is taken as an example of application for three objective functions. In addition, a fuzzy decision maker is applied to select the best solution along the pareto front based on the defined criteria. The results are compared to the traditional optimization, and collaborative optimization formulations that do not use multi-objective particle swarm optimization. It is shown that the integration of multi-objective particle swarm optimization into collaborative optimization provides an efficient framework for design and analysis of hierarchical multidisciplinary design optimization problems.

A Regularized Inexact Penalty Decomposition Algorithm for Multidisciplinary Design Optimization Problems With Complementarity Constraints

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Shen Lu ◽  
Harrison M. Kim
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Original Problem ◽  
Equilibrium Problems ◽  
Optimization Problems ◽  
Decomposition Algorithm ◽  
Multidisciplinary Design ◽  
Stationary Points ◽  
Complementarity Constraints ◽  
Regularization Technique

Economic and physical considerations often lead to equilibrium problems in multidisciplinary design optimization (MDO), which can be captured by MDO problems with complementarity constraints (MDO-CC)—a newly emerging class of problem. Due to the ill-posedness associated with the complementarity constraints, many existing MDO methods may have numerical difficulties solving this class of problem. In this paper, we propose a new decomposition algorithm for the MDO-CC based on the regularization technique and inexact penalty decomposition. The algorithm is presented such that existing proofs can be extended, under certain assumptions, to show that it converges to stationary points of the original problem and that it converges locally at a superlinear rate. Numerical computation with an engineering design example and several analytical example problems shows promising results with convergence to the all-in-one solution.

A Sequential Linear Programming Coordination Algorithm for Analytical Target Cascading

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Jeongwoo Han ◽  
Panos Y. Papalambros
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Trust Region Method ◽  
Trust Region ◽  
Test Problems ◽  
Analytical Target Cascading ◽  
Step Size ◽  
Coordination Strategy ◽  
Target Cascading ◽  
Solution Accuracy

Decomposition-based strategies, such as analytical target cascading (ATC), are often employed in design optimization of complex systems. Achieving convergence and computational efficiency in the coordination strategy that solves the partitioned problem is a key challenge. A new convergent strategy is proposed for ATC that coordinates interactions among subproblems using sequential linearizations. The linearity of subproblems is maintained using infinity norms to measure deviations between targets and responses. A subproblem suspension strategy is used to suspend temporarily inclusion of subproblems that do not need significant redesign, based on trust region and target value step size. An individual subproblem trust region method is introduced for faster convergence. The proposed strategy is intended for use in design optimization problems where sequential linearizations are typically effective, such as problems with extensive monotonicities, a large number of constraints relative to variables, and propagation of probabilities with normal distributions. Experiments with test problems show that, relative to standard ATC coordination, the number of subproblem evaluations is reduced considerably while the solution accuracy depends on the degree of monotonicity and nonlinearity.

Variable-Fidelity Multidisciplinary Design Optimization Based on Analytical Target Cascading Framework

2012 ◽  
Vol 544 ◽  
pp. 49-54 ◽  
Author(s):  
Jun Zheng ◽  
Hao Bo Qiu ◽  
Xiao Lin Zhang
Keyword(s):  
Multidisciplinary Design Optimization ◽  
Model Building ◽  
Computational Cost ◽  
Simulation Models ◽  
Multidisciplinary Design ◽  
High Fidelity ◽  
Analytical Target Cascading ◽  
Approximation Model ◽  
Target Cascading ◽  
Variable Fidelity

ATC provides a systematic approach in solving decomposed large scale systems that has solvable subsystems. However， complex engineering system usually has a high computational cost , which result in limiting real-life applications of ATC based on high-fidelity simulation models. To address these problems, this paper aims to develop an efficient approximation model building techniques under the analytical target cascading (ATC) framework, to reduce computational cost associated with multidisciplinary design optimization problems based on high-fidelity simulations. An approximation model building techniques is proposed: approximations in the subsystem level are based on variable-fidelity modeling (interaction of low- and high-fidelity models). The variable-fidelity modeling consists of computationally efficient simplified models (low-fidelity) and expensive detailed (high-fidelity) models. The effectiveness of the method for modeling under the ATC framework using variable-fidelity models is studied. Overall results show the methods introduced in this paper provide an effective way of improving computational efficiency of the ATC method based on variable-fidelity simulation models.

Multidisciplinary Design Optimization for Small Vertical Wind Turbine Design

2014 ◽  
Vol 571-572 ◽  
pp. 1083-1086
Author(s):  
Qiu Yun Mo ◽  
Fei Deng ◽  
Shuai Shuai Li ◽  
Ke Yan Zhang
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Design Theory ◽  
Optimization Problems ◽  
Vertical Wind ◽  
Multidisciplinary Design ◽  
Existing Problems ◽  
Depth Study ◽  
Turbine Design

Multidisciplinary design optimization (MDO) represents the development direction of complex products design theory and method, it shows a huge advantage in solving complex optimization problems in engineering applications, for example product design. This paper briefly analyzes some existing problems of small vertical wind turbine, and puts forward using the theory of MDO in small vertical wind turbine structural optimization. Then,the paper analyzes and points out the key technology of using MDO theory to optimize small vertical wind turbine, and provides a new train of thought for further in-depth study of small vertical wind turbine to improve the overall performance of the small vertical wind turbine products.

Interaction balance optimization in multidisciplinary design optimization problems

2015 ◽  
Vol 24 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Debiao Meng ◽  
Xiaoling Zhang ◽  
Yuan-Jian Yang ◽  
Huanwei Xu ◽  
Hong-Zhong Huang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Problems ◽  
Multidisciplinary Design ◽  
Interaction Balance
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