[ACM Press the 8th annual conference - Seattle, Washington, USA (2006.07.08-2006.07.12)] Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06 - A GA-based method to produce generalized hyper-heuristics for the 2D-regular cutting stock problem

✍ Scribed by Terashima-Marín, H.; Farías Zárate, C. J.; Ross, P.; Valenzuela-Rendón, M.

• Book ID: 121494725
• Publisher: ACM Press
• Year: 2006
• Tongue: English
• Weight: 169 KB
• Category: Article
• ISBN-13: 9781595931863
• DOI: 10.1145/1143997.1144102

✦ Synopsis

The idea behind hyper-heuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. To be worthwhile, such combination should outperform the single heuristics. This paper presents a GAbased method that produces general hyper-heuristics that solve two-dimensional cutting stock problems. The GA uses a variable-length representation, which evolves combinations of condition-action rules producing hyper-heuristics after going through a learning process which includes training and testing phases. Such hyper-heuristics, when tested with a large set of benchmark problems, produce outstanding results (optimal and near-optimal) for most of the cases. The testebed is composed of problems used in other similar studies in the literature. Some additional instances of the testbed were randomly generated.