A hyper-heuristic for solving one and two-dimensional bin packing problems

Authors:
Eunice López-Camacho;Hugo Terashima-Marín;Peter Ross
Affiliations:
ITESM, Monterrey, Nuevo León, Mexico;ITESM, Monterrey, Nuevo León, Mexico;Napier University, Edinburgh, United Kingdom
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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Abstract

The idea behind hyper-heuristics is to discover rules that relate different problem states with the best single heuristic to apply. This investigation works towards extending the problem domain in which a given hyper-heuristic can be applied and implements a framework to generate hyper-heuristics for a wider range of bin packing problems. We present a GA-based method that produces general hyper-heuristics that solve a variety of instances of one- and two dimensional bin packing problem without further parameter tuning. The two-dimensional problem instances considered deal with rectangles, convex and non-convex polygons.