Emilia Tantar

A priori landscape analysis in guiding interactive multi-objective metaheuristics

The integration of information provided by an a priori landscape analysis as a guiding tool for interactive EMO methods is proposed. For this purpose, a new type of a priori landscape analysis is introduced, namely ellipse enclosure of the feasible solutions set in the solution space. The interaction takes place in the solution space, the user having as visual guiding tools the computed enclosure as well as the set of solutions found at the previous search phase. Furthermore, reference points are specified by the user thus directing the search. The effectiveness and efficiency of the method are supported through statistical experimentation performed on the bi-objective permutation flow shop problem.

Application of a Particle Filter-Based Subset Simulation Method to the Reliability Assessment of a Marine Structure

The present study aims at investigating advanced subset simulation techniques, which are based on the theory of particle filter, for the assessment of the failure probability of a marine structure under extreme loading conditions. Three approaches are considered, namely the classical particle filter method, the subset simulation with a branching process and one using the minimum values of the samples as levels. They are, first, intensively applied on a simple example for which a known analytical solution is available, in order to investigate their parameter settings. Then, they are applied, with good performance, using their respective best parameter settings, to the assessment of failure probability of a FPSO subjected to extreme roll motion.