Target Exploration for Disconnected Feasible Regions in Enterprise-Driven Multilevel Product Design

Kim, Hyung Min; Kumar, Deepak; Chen, Wei; Papalambros, Panos Y.

doi:10.2514/1.13908

Cited by 25 publications

(8 citation statements)

References 25 publications

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“…We expect that the analytical target cascading method (ATC, Kim 2001) may experience similar difficulties since it is a subclass of ALC. In fact, the difficulties associated with disconnected feasible domains have been observed for ATC by Kim and Papalambros (2006). Other coordination approaches that use alternating minimization such as MDOIS (Shin and Park 2005), BLISS (Sobieszczanski- Sobieski et al 2000), and enhanced collaborative optimization (Roth and Kroo 2008) may also be affected by the behavior of the sequential process.…”

Section: Discussionmentioning

confidence: 99%

Multi-modality in augmented Lagrangian coordination for distributed optimal design

Tosserams

Etman

Rooda

2009

Struct Multidisc Optim

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This paper presents an empirical study of the convergence characteristics of augmented Lagrangian coordination (ALC) for solving multi-modal optimization problems in a distributed fashion. A number of test problems that do not satisfy all assumptions of the convergence proof for ALC are selected to demonstrate the convergence characteristics of ALC algorithms. When only a local search is employed at the subproblems, local solutions to the original problem are often attained. When a global search is performed at subproblems, global solutions to the original, nondecomposed problem are found for many of the examples. Although these findings are promising, ALC with a global subproblem search may yield only local solutions in the case of non-convex coupling functions or disconnected feasible domains. Results indicate that for these examples both the starting point and the sequence in which subproblems are solved determines which solution is obtained. We illustrate that the main cause for this behavior lies in the alternating minimization inner loop, which is inherently of a local nature.

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Section: Discussionmentioning

confidence: 99%

Multi-modality in augmented Lagrangian coordination for distributed optimal design

Tosserams

Etman

Rooda

2009

Struct Multidisc Optim

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“…Second, objective function dynamics might cause the global optima to switch from one disconnected feasible region to another on problems with disconnected feasible regions, which are very common in real-world constrained problems, especially the scheduling problems [11]- [13]. Third, in problems with fixed objective functions and dynamic constraints, the changing infeasible areas might expose new, better global optima without changing the existing optima.…”

Section: Characteristics Of Real-world Dynamicmentioning

confidence: 97%

Continuous Dynamic Constrained Optimization—The Challenges

Nguyễn

Yao

2012

IEEE Trans. Evol. Computat.

102

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Many real-world dynamic problems have constraints, and in certain cases not only the objective function changes over time, but also the constraints. However, there is no research in answering the question of whether current algorithms work well on continuous dynamic constrained optimization problems (DCOPs), nor is there any benchmark problem that reflects the common characteristics of continuous DCOPs. This paper contributes to the task of closing this gap. We will present some investigations on the characteristics that might make DCOPs difficult to solve by some existing dynamic optimization (DO) and constraint handling (CH) algorithms. We will then introduce a set of benchmark problems with these characteristics and test several representative DO and CH strategies on these problems. The results confirm that DCOPs do have special characteristics that can significantly affect algorithm performance. The results also reveal some interesting observations where the presence or combination of different types of dynamics and constraints can make the problems easier to solve for certain types of algorithms. Based on the analyses of the results, a list of potential requirements that an algorithm should meet to solve DCOPs effectively will be proposed.

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“…The enterprise-driven multilevel vehicle suspension model was originally presented in [37] to demonstrate the use of a decision-based multilevel optimization formulation in designing hierarchical systems. The 3-level hierarchical vehicle suspension model is modified slightly here by fixing the front and rear linear coil spring stiffnesses (K LF and K LR ) to ensure the submodels at the same level are independent (see Figure 7).…”

Section: An Enterprise-driven Multilevel Vehicle Suspension Modelmentioning

confidence: 99%

“…where E and G characterize the rigidity of the spring material. More details can be found in [37]. When applying the proposed HSSA method, all the models are treated as a black-box type of functions.…”

Section: An Enterprise-driven Multilevel Vehicle Suspension Modelmentioning

confidence: 99%

A Hierarchical Statistical Sensitivity Analysis Method for Complex Engineering Systems Design

Yin

Chen

2008

Journal of Mechanical Design

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The method of Statistical Sensitivity Analysis (SSA) is playing an increasingly important role in engineering design, especially with the consideration of uncertainty. However, applying SSA to the design of complex engineering systems is not straight forward due to both computational and organizational difficulties. In this paper, a Hierarchical Statistical Sensitivity Analysis (HSSA) method is developed to facilitate the application of SSA to the design of complex systems especially those follow hierarchical modeling structures. A top-down strategy for HSSA is introduced to only invoke the SSA of critical submodels based on the significance of submodel performances. A simplified formulation of the Global Statistical Sensitivity Index (GSSI) is studied to represent the effect of a lower-level submodel input on a higher-level model response by aggregating the submodel SSA results across intermediate levels. A sufficient condition under which the simplified formulation provides an accurate solution is derived. To improve the accuracy of the GSSI formulation for a general situation, a modified formulation is proposed by including an Adjustment Coefficient (AC) to capture the impact of the nonlinearities of the upper level models. To save cost, the evaluation of the AC shares the same set of samplings used in the submodel SSA. The proposed HSSA method is examined through mathematical examples and a 3-level hierarchical model used in vehicle suspension systems design.

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Target Exploration for Disconnected Feasible Regions in Enterprise-Driven Multilevel Product Design

Cited by 25 publications

References 25 publications

Multi-modality in augmented Lagrangian coordination for distributed optimal design

Multi-modality in augmented Lagrangian coordination for distributed optimal design

Continuous Dynamic Constrained Optimization—The Challenges

A Hierarchical Statistical Sensitivity Analysis Method for Complex Engineering Systems Design

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