A framework to hybridize PBIL and a hyper-heuristic for dynamic environments

Authors:
Gönül Uludağ;Berna Kiraz;A. Şima Etaner-Uyar;Ender Özcan
Affiliations:
Istanbul Technical University, Turkey;Istanbul Technical University, Turkey;Istanbul Technical University, Turkey;University of Nottingham, UK
Venue:
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Year:
2012

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Abstract

Selection hyper-heuristic methodologies explore the space of heuristics which in turn explore the space of candidate solutions for solving hard computational problems. This study investigates the performance of approaches based on a framework that hybridizes selection hyper-heuristics and population based incremental learning (PBIL), mixing offline and online learning mechanisms for solving dynamic environment problems. The experimental results over well known benchmark instances show that the approach is generalized enough to provide a good average performance over different types of dynamic environments.