An efficient hyperheuristic for strip-packing problems

Ignacio Araya, Bertrand Neveu, María Cristina Riff

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

17 Scopus citations


In this paper we introduce a hyperheuristic to solve hard strip packing problems. The hyperheuristic manages a sequence of greedy low-level heuristics, each element of the sequence placing a given number of objects. A low-level solution is built by placing the objects following the sequence of low-level heuristics. The hyperheuristic performs a hill-climbing algorithm on this sequence by testing different moves (adding, removing, replacing a low-level heuristic). The results we obtained are very encouraging and improve the results from the single heuristics tests. Thus, we conclude that the collaboration among heuristics is an interesting approach to solve hard strip packing problems.

Original languageEnglish
Title of host publicationAdaptive and Multilevel Metaheuristics
EditorsCarlos Cotta, Marc Sevaux, Kenneth Sörensen
Number of pages16
StatePublished - 2008
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X


  • Hill climbing
  • Hyperheuristic
  • Low-level heuristic
  • Strip packing problems


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