Efficient multi-level design optimization using analytical target cascading and sequential quadratic programming

2011 ◽  
Vol 44 (3) ◽  
pp. 351-362 ◽  
Author(s):  
Paolo Guarneri ◽  
Massimiliano Gobbi ◽  
Panos Y. Papalambros
Keyword(s):  
Quadratic Programming ◽  
Design Optimization ◽  
Sequential Quadratic Programming ◽  
Analytical Target Cascading ◽  
Target Cascading ◽  
Multi Level ◽  
Level Design

Multi‐level design optimization using target cascading, an improvement of convergence

2009 ◽  
Vol 28 (5) ◽  
pp. 1162-1178 ◽  
Author(s):  
F. Moussouni ◽  
S. Kreuawan ◽  
S. Brisset ◽  
F. Gillon ◽  
P. Brochet ◽  
...  
Keyword(s):  
Design Optimization ◽  
Target Cascading ◽  
Multi Level ◽  
Level Design

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.

scholarly journals Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems

2014 ◽  
Author(s):  
Bo Yang Yu ◽  
Tomonori Honda ◽  
Syed Zubair ◽  
Mostafa H. Sharqawy ◽  
Maria C. Yang
Keyword(s):  
Optimal Design ◽  
Complex Systems ◽  
Design Optimization ◽  
Reverse Osmosis ◽  
Large Scale ◽  
Analytical Target Cascading ◽  
Total Water ◽  
Target Cascading ◽  
Desalination Plants ◽  
Functional Components

Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of sub-system hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system’s functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions.

Design Methods for Integrated Design of Blast Resistance Panels and Materials

2013 ◽  
Author(s):  
Sungwoo Jang ◽  
Hae-Jin Choi
Keyword(s):  
Material Selection ◽  
Blast Resistance ◽  
Integrated Design ◽  
Design Methods ◽  
Design Approach ◽  
Target Cascading ◽  
Conventional Material ◽  
Multi Level ◽  
Level Design ◽  
Product Layout

Integrated Materials and Products Design (IMPD) differs in the way that materials as well as product layout are designed or optimized in a concurrent manner to meet design requirements. IMPD allows the specific performance required in a product to be achieved by tailoring materials and product, since system performance will not be limited by a pre-chosen material employed in conventional, material-selection-based design. In this study, Blast Resistance Panels (BRPs) with square honeycomb core are designed based on this new design approach to further enhance the performance of BRPs. We employ multi-level design methods for the integrated design of blast resistance panels and materials. Along with the traditional multi-level optimization of BRP, another design approach, Analytical Target Cascading (ATC) is introduced for a comparative design study in the BRP design. In this article, we compare the design results and design exploration efficiency of the two multi-level design methods in designing the blast resistance panels as well as those materials. We also discuss the advantage and disadvantage of the methods observed in this study.

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.

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