This article describes a grammar-based hyper-heuristic model for selecting heuristics to solve the two-dimensional bin packing problem (2D-PBB) with irregular pieces and regular objects. We propose to use a genetic programming approach to generate rules for selecting one suitable heuristic according to the features that characterize the problem state. The experiments confirm the idea that the results produced by the proposed approach are able to rival those obtained by some heuristics described in the literature.
['Alejandro Sosa-Ascencio', 'Hugo Terashima-Marín', 'José Carlos Ortiz-Bayliss', 'Santiago Enrique Conant-Pablos']
Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems