Chance constraints represent a popular tool for finding decisions that enforce the
satisfaction of random inequality systems in terms of probability. They are widely used in …

Uncertainty is prevalent in engineering design, statistical learning, and decision making
broadly. Due to inherent risk-averseness and ambiguity about assumptions, it is common to …

Topology optimization of structures is nowadays a well developed field with many different
approaches and a wealth of applications. One of the earliest methods of topology …

This work proposes a stochastic shape optimization method for continuous structures using
the level-set method. Such a method aims to minimize the expected compliance and its …

This work proposes a level-set based approach for solving risk-averse structural topology
optimization problems considering random field loading and material uncertainty. The use of …

This paper deals with shape optimization for elastic materials under stochastic loads. It
transfers the paradigm of stochastic dominance, which allows for flexible risk aversion via …

We consider a shape optimization problem for an elliptic partial differential equation with
uncertainty in its input data. The design variable enters the lower-order term of the state …

A novel approach for risk-averse structural topology optimization under uncertainties is
presented, which takes into account stochastic data of the state equation, specifically …

We present an efficient algorithm to find an optimal fiber orientation in composite materials.
Within a two-scale setting fiber orientation is regarded as a function in space on the …

The nonlinear stochastic programming problem involving CVaR in the objective and
constraints is considered. Solving the latter problem in a framework of bi-level stochastic …