Probabilistic Analytical Target Cascading: A Moment Matching Formulation for Multilevel Optimization Under Uncertainty
نویسندگان
چکیده
Analytical target cascading (ATC) is a methodology for hierarchical multilevel system design optimization. In previous work, the deterministic ATC formulation was extended to account for random variables represented by expected values to be matched among subproblems and thus ensure design consistency. In this work, the probabilistic formulation is augmented to allow the introduction and matching of additional probabilistic characteristics. A particular probabilistic analytical target cascading (PATC) formulation is proposed that matches the first two moments of interrelated responses and linking variables. Several implementation issues are addressed, including representation of probabilistic design targets, matching responses and linking variables under uncertainty, and coordination strategies. Analytical and simulation-based optimal design examples are used to illustrate the new formulation. The accuracy of the proposed PATC formulation is demonstrated by comparing PATC results to those obtained using a probabilistic all-in-one formulation. DOI: 10.1115/1.2205870
منابع مشابه
Techniques for Estimating Uncertainty Propagation in Probabilistic Design of Multilevel Systems
In probabilistic design of multilevel systems, the challenge is to estimate uncertainty propagation since outputs of subsystems at lower levels constitute inputs of subsystems at higher levels. Three uncertainty propagation estimation techniques are compared in this paper in terms of numerical efficiency and accuracy: root sum square (linearization), distribution-based moment approximation, and...
متن کاملAn SLP Filter Algorithm for Probabilistic Analytical Target Cascading
Decision-making under uncertainty is particularly challenging in the case of multidisciplinary, multilevel system optimization problems. Subsystem interactions cause strong couplings, which may be amplified by uncertainty. Thus, effective coordination strategies can be particularly beneficial. Analytical target cascading (ATC) is a deterministic optimization method for multilevel hierarchical s...
متن کاملDesign Optimization of Hierarchically Decomposed Multilevel Systems under Uncertainty
This paper presents a methodology for design optimization of decomposed systems in the presence of uncertainties. We extend the analytical target cascading (ATC) formulation to probabilistic design by treating stochastic quantities as random variables and parameters and posing reliability-based design constraints. We model the propagation of uncertainty throughout the multilevel hierarchy of el...
متن کاملOptimal Multilevel System Design under Uncertainty
In this paper we consider hierarchically decomposed multilevel systems, and extend previous deterministic methodologies for optimal and consistent design of such systems to account for the presence of uncertainties. Specifically, we use the probabilistic formulation of the analytical target cascading process to solve the multilevel problem, and use an advanced mean value-based technique to esti...
متن کاملRobustness-based portfolio optimization under epistemic uncertainty
In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...
متن کامل