Analytical target cascading based synergistic cell formation model in e-manufacturing system for mass customization

2007 ◽  
Vol 43 (02) ◽  
pp. 178 ◽  
Author(s):  
Gang ZHAO
Keyword(s):  
Mass Customization ◽  
Manufacturing System ◽  
Cell Formation ◽  
Analytical Target Cascading ◽  
Formation Model ◽  
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.

scholarly journals Analytical target cascading for optimal configuration of cloud manufacturing services

2017 ◽  
Vol 151 ◽  
pp. 330-343 ◽  
Author(s):  
Yingfeng Zhang ◽  
Geng Zhang ◽  
Ting Qu ◽  
Yang Liu ◽  
Ray Y. Zhong
Keyword(s):  
Cloud Manufacturing ◽  
Optimal Configuration ◽  
Analytical Target Cascading ◽  
Target Cascading

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.

Diagonal Quadratic Approximation for Parallelization of Analytical Target Cascading

2008 ◽  
Vol 130 (5) ◽  
Author(s):  
Yanjing Li ◽  
Zhaosong Lu ◽  
Jeremy J. Michalek
Keyword(s):  
Optimization Problems ◽  
Computational Cost ◽  
Descent Method ◽  
Quadratic Approximation ◽  
Test Problems ◽  
Analytical Target Cascading ◽  
Decomposition Approach ◽  
Diagonal Quadratic Approximation ◽  
Target Cascading ◽  
Nested Loop

Analytical target cascading (ATC) is an effective decomposition approach used for engineering design optimization problems that have hierarchical structures. With ATC, the overall system is split into subsystems, which are solved separately and coordinated via target/response consistency constraints. As parallel computing becomes more common, it is desirable to have separable subproblems in ATC so that each subproblem can be solved concurrently to increase computational throughput. In this paper, we first examine existing ATC methods, providing an alternative to existing nested coordination schemes by using the block coordinate descent method (BCD). Then we apply diagonal quadratic approximation (DQA) by linearizing the cross term of the augmented Lagrangian function to create separable subproblems. Local and global convergence proofs are described for this method. To further reduce overall computational cost, we introduce the truncated DQA (TDQA) method, which limits the number of inner loop iterations of DQA. These two new methods are empirically compared to existing methods using test problems from the literature. Results show that computational cost of nested loop methods is reduced by using BCD, and generally the computational cost of the truncated methods is superior to the nested loop methods with lower overall computational cost than the best previously reported results.

Sign in / Sign up

Export Citation Format

Share Document