TY - JOUR
T1 - A strip packing solving method using an incremental move based on maximal holes
AU - Neveu, Bertrand
AU - Trombettoni, Gilles
AU - Araya, Ignacio
AU - Riff, Maria Cristina
N1 - Funding Information:
To validate our alternative approach, we have designed an incremental move, maintaining maximal holes, for the strip packing problem, a variant of the famous 2D bin-packing. We have also implemented a metaheuristic, with no user-defined parameter, using this move and standard greedy heuristics. We have finally designed two variants of this incomplete method. In the first variant, a better first layout is provided by a ∗With the financial support of CONICYT and INRIA. †COPRIN team, INRIA Sophia-Antipolis, ENPC, France ‡COPRIN team, University of Nice-Sophia, INRIA, France §Department of Computer Science, Universitad Técnica Federico Santa Maria, Valparaiso, Chile ¶Department of Computer Science, Universitad Técnica Federico Santa Maria, Valparaiso, Chile
PY - 2008/10
Y1 - 2008/10
N2 - When handling 2D packing problems, numerous incomplete and complete algorithms maintain a so-called bottom-left (BL) property: no rectangle placed in a container can be moved more left or bottom. While it is easy to make a rectangle BL when it is added in a container, it is more expensive to maintain all the placed pieces BL when a rectangle is removed. This prevents researchers from designing incremental moves for metaheuristics or efficient complete optimization algorithms. This paper investigates the possibility of violating the BL property. Instead, we propose to maintain the set of maximal holes, which allows incremental additions and removals of rectangles. To validate our alternative approach, we have designed an incremental move, maintaining maximal holes, for the strip packing problem, a variant of the famous 2D bin-packing. We have also implemented a metaheuristic, with no user-defined parameter, using this move and standard greedy heuristics. We have finally designed two variants of this incomplete method. In the first variant, a better first layout is provided by a hyperheuristic proposed by some of the authors. In the second variant, a fast repacking procedure recovering the BL property is occasionally called during the local search. Experimental results show that the approach is competitive with the best known incomplete algorithms.
AB - When handling 2D packing problems, numerous incomplete and complete algorithms maintain a so-called bottom-left (BL) property: no rectangle placed in a container can be moved more left or bottom. While it is easy to make a rectangle BL when it is added in a container, it is more expensive to maintain all the placed pieces BL when a rectangle is removed. This prevents researchers from designing incremental moves for metaheuristics or efficient complete optimization algorithms. This paper investigates the possibility of violating the BL property. Instead, we propose to maintain the set of maximal holes, which allows incremental additions and removals of rectangles. To validate our alternative approach, we have designed an incremental move, maintaining maximal holes, for the strip packing problem, a variant of the famous 2D bin-packing. We have also implemented a metaheuristic, with no user-defined parameter, using this move and standard greedy heuristics. We have finally designed two variants of this incomplete method. In the first variant, a better first layout is provided by a hyperheuristic proposed by some of the authors. In the second variant, a fast repacking procedure recovering the BL property is occasionally called during the local search. Experimental results show that the approach is competitive with the best known incomplete algorithms.
KW - 2D packing
KW - Bin packing
KW - Local search
KW - Strip packing
UR - http://www.scopus.com/inward/record.url?scp=55849108123&partnerID=8YFLogxK
U2 - 10.1142/S0218213008004205
DO - 10.1142/S0218213008004205
M3 - Article
AN - SCOPUS:55849108123
SN - 0218-2130
VL - 17
SP - 881
EP - 901
JO - International Journal on Artificial Intelligence Tools
JF - International Journal on Artificial Intelligence Tools
IS - 5
ER -