Point estimates of the parameters in real world models convey valuable information about the actual system. However, parameter comparisons and/or statistical inference requires de...
In the Sesame framework, we develop a modeling and simulation environment for the efficient design space exploration of heterogeneous embedded systems. Since Sesame recognizes se...
With the popularity of efficient multi-objective evolutionary optimization (EMO) techniques and the need for such problem-solving activities in practice, EMO methodologies and EMO ...
With the advent of efficient techniques for multi-objective evolutionary optimization (EMO), real-world search and optimization problems are being increasingly solved for mulitple ...
Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective O...