Within the robust design optimization, the statistical variability of the design parameter is considered. The most general method for solving optimization problems under uncertainties is the well established Monte Carlo simulation method. However, the major shortcoming of this approach is its vast need of computational resources (the number of solver runs required), and these cannot be presumed...

Various criteria have been considered in the literature for selection of optimal sensor networks. Amongst these, maximization of network reliability is an important criterion. While there are several approaches for designing maximum reliability networks, uncertainty in the available sensor reliability data has not been considered in these designs. In this article we present two novel formulatio...

Optimization Methods for Power Grid Reliability

This paper proposes an adaptive hybrid genetic algorithm (aHGA) for effectively solving the complex reliability optimization problems. The proposed aHGA uses a local search technique and an adaptive scheme for respectively constructing hybrid algorithm and adaptive ability. For more various comparisons with the proposed adaptive algorithm, other aHGAs with conventional adaptive schemes are cons...

In reliability engineering focused on the design and optimization of structures, the typical measure of reliability is the probability of failure of the structure or its individual components relative to specific limit states. However, the failure probability has troublesome properties that raise several theoretical, practical, and computational issues. This paper explains the seriousness of th...