This paper addresses a constrained two-dimensional (2D), non-guillotine restricted, packing problem, where a fixed set of small rectangles has to be packed into a larger stock rectangle so as to maximize the value of the rectangles packed. The algorithm we propose hybridizes a novel placement procedure with a genetic algorithm based on random keys. We propose also a new fitness function to drive the optimization. The approach is tested on a set of instances taken from the literature and compared with other approaches. The experimental results validate the quality of the solutions and the effectiveness of the proposed algorithm.
AT&T Labs Research Technical Report TD-7M7QJG, AT&T Labs Research, Florham Park, NJ 07932, December 10, 2008.
View A multi-population genetic algorithm for a constrained two-dimensional orthogonal packing problem