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 problems with meta-heuristic algorithms. As packing tasks are combinatorial problems with very large search spaces, the recent literature encourages the use of meta-heuristic search methods, in particular genetic algorithms. The objective of this paper is to present and categorise the solution approaches in the literature for 2D regular and irregular strip packing problems. The focus is hereby on the analysis of the methods involving genetic algorithms. An overview of the methods applying other meta-heuristic algorithms including simulated annealing, tabu search, and artificial neural networks is also given.
meta-heuristics packing problem genetic algorithms regular irregular simulated annealing tabu search artificial neural networks two-dimensional