Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
The problem of short-term scheduling under uncertainty is addressed in this paper through a multiobjective optimization framework that incorporates economic expectation, robustnes...
In multicriteria optimization, several objective functions, conflicting with each other, have to be minimized simultaneously. We propose a new efficient method for approximating t...
This work presents a discriminative training method for
particle filters in the context of multi-object tracking. We
are motivated by the difficulty of hand-tuning the many
mode...
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...