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Improving local-search metaheuristics through look-ahead policies

  • David Meignan
  • Silvia Schwarze
  • Stefan Voß
Article
  • 248 Downloads

Abstract

As a basic principle, look-ahead approaches investigate the outcomes of potential future steps to evaluate the quality of alternative search directions. Different policies exist to set up look-ahead methods differing in the object of inspection and in the extensiveness of the search. In this work, two original look-ahead strategies are developed and tested through numerical experiments. The first method introduces a look-ahead mechanism that acts as a hyper-heuristic for comparing and selecting local-search operators. The second method uses a look-ahead strategy on a lower level in order to guide a local-search metaheuristic. The proposed approaches are implemented using a hyper-heuristic framework. They are tested against alternative methods using two different competition benchmarks, including a comparison with results given in literature. Furthermore, in a second set of experiments, a detailed investigation regarding the influence of particular parameter values is executed for one method. The experiments reveal that the inclusion of a simple look-ahead principle into an iterated local-search procedure significantly improves the outcome regarding the considered benchmarks.

Keywords

Metaheuristic Hyper-heuristic Look-ahead Iterated local-search 

Mathematics Subject Classifications (2010)

68T20 90B40 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Mathematics and Computer ScienceUniversity of OsnabrückOsnabrückGermany
  2. 2.Institute of Information Systems, University of HamburgHamburgGermany
  3. 3.Escuela de Ingeniería IndustrialPontificia Universidad Católica de ValparaísoValparaísoChile

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