Fair-share ILS
Steven Adriænsen, Tim Brys, Ann Nowé · 2014
In this work we present a simple state-of-the-art selection hyperheuristic called Fair-Share Iterated Local Search (FS-ILS). FS-ILS is an iterated local search method using a conservative restart condition. Each iteration, a perturbation heuristic is selected proportionally to the acceptance rate of its previously proposed candidate solutions (after iterative improvement) by a domain-independent variant of the Metropolis condition. FS-ILS was developed in prior work using a semi-automated design approach. That work focused on how the method was found, rather than the method itself. As a result, it lacked a detailed explanation and analysis of the method, which will be the main contribution of this work. In our experiments we analyze FS-ILS's parameter sensitivity, accidental complexity and compare it to the contestants of the CHeSC (2011) competition.