A review of the application of meta-heuristic algorithms to 2D strip packing problems

This paper is a review of the approaches developed to solve 2D packing prob lems with meta-heuristic algorithms. As packing tasks are combinatorial pro blems with very large search spaces, the recent literature encourages the u se of meta-heuristic search methods, in particular genetic algorithms. The objective of this paper is to present and categorise the solution approache s in the literature for 2D regular and irregular strip packing problems. Th e focus is hereby on the analysis of the methods involving genetic algorith ms. An overview of the methods applying other meta-heuristic algorithms inc luding simulated annealing, tabu search, and artificial neural networks is also given.