In this paper, we study the perturbation operator of Iterated Local Search. To guide more efficiently the search to move towards new promising regions of the search space, we intro...
In combinatorial solution spaces Iterated Local Search (ILS) turns out to be exceptionally successful. The question arises: is ILS also capable of improving the optimization proces...
An important challenge within hyper-heuristic research is to design search methodologies that work well, not only across different instances of the same problem, but also across di...
Edmund K. Burke, Timothy Curtois, Matthew R. Hyde,...
This paper presents a novel approach to continuously and robustly tracking critical (geometrically, perpendicular and/or extremal) distances from a moving plane point p ∈ R2 to a...
Xianming Chen, Elaine Cohen, Richard F. Riesenfeld
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...