In this paper we examine multi-objective linear programming problems in the face of data
uncertainty both in the objective function and the constraints. First, we derive a formula for …

Smart power grids are transitioning towards effective employment of distributed energy
resources including renewable energy sources to address the growing environmental …

Performance metrics are essential for quantifying the performance of optimization algorithms
in the field of evolutionary multi-objective optimization. Such metrics allow researchers to …

In this paper we present new concepts of efficiency for uncertain multi-objective optimization
problems. We analyze the connection between the concept of minmax robust efficiency …

The paper addresses the parametric design and multi-objective optimisation of ships under
uncertainty, applying the Holistic Optimisation Design Approach. The methodology starts …

This paper investigates robust design optimization of truss structures with uncertain-but-
bounded parameters and loads. The variations of the cross-sectional areas, Young's moduli …

In some special engineering cases, the lower and upper bounds of uncertain parameters
are appropriately quantified as fuzzy variables instead of deterministic values. To address …

Robust optimisation refers to the process of finding optimal solutions that have the lowest
sensitivity to possible perturbations. In a multi-objective search space the robust optimal …

Water quality deterioration in water distribution networks can be associated with high water
residence time in the network. To this end, some previous studies have proposed …

The main objective here is an engineering optimization of the truss-type structures using the
generalized perturbation-based Stochastic Finite Element Method. This procedure is based …