Recent works in evolutionary multiobjective optimization suggest to shift the focus from solely evaluating optimization success in the objective space to also taking the decision s...
This paper presents four rotatable multi-objective test problems that are designed for testing EMO (Evolutionary Multiobjective Optimization) algorithms on their ability in dealin...
Data allocation is a key performance factor for parallel database systems (PDBS). This holds especially for data warehousing environments where huge amounts of data and complex an...
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
We address the problem of coordinating the plans and schedules for a team of agents in an uncertain and dynamic environment. Bounded rationality, bounded communication, subjectivi...