Multi-objectivization has been used to solve several single objective problems with improved results over traditional genetically inspired optimization methods. Multi-objectivization reformulates the single objective problem into a multiple objective problem. The reformulated problem is then...

We study generalizations of parallel tempering, also known as replica exchange method, that aim at maximizing the sampling of independent low energy configurations through enforcing random walks in temperature (or other control variables). The advantage of these techniques is the easily tunable...

The structure of the search space explains the behavior of multiobjective search algorithms, and helps to design well-performing approaches. In this work, we analyze the properties of multiobjective combinatorial search spaces, and we pay a particular attention to the correlation between the...