Solving the Rectangle Packing Problem by an Iterative Hybrid Heuristic

Author(s):  
David Beltrán-Cano ◽  
Belén Melián-Batista ◽  
J. Marcos Moreno-Vega
2002 ◽  
Vol 141 (2) ◽  
pp. 341-358 ◽  
Author(s):  
Yu-Liang Wu ◽  
Wenqi Huang ◽  
Siu-chung Lau ◽  
C.K Wong ◽  
Gilbert H Young

2007 ◽  
Vol 24 (04) ◽  
pp. 463-478 ◽  
Author(s):  
DUANBING CHEN ◽  
WENQI HUANG

The constrained rectangle-packing problem is the problem of packing a subset of rectangles into a larger rectangular container, with the objective of maximizing the layout value. It has many industrial applications such as shipping, wood and glass cutting, etc. Many algorithms have been proposed to solve it, for example, simulated annealing, genetic algorithm and other heuristic algorithms. In this paper a new heuristic algorithm is proposed based on two strategies: the rectangle selecting strategy and the rectangle packing strategy. We have applied the algorithm to 21 smaller, 630 larger and other zero-waste instances. The computational results demonstrate that the integrated performance of the algorithm is rather satisfying and the algorithm developed is fairly efficient for solving the constrained rectangle-packing problem.


1998 ◽  
Vol 108 (3) ◽  
pp. 509-526 ◽  
Author(s):  
Gubtram Scheithauer ◽  
Uta Sommerweiß

2013 ◽  
Vol 93 (107) ◽  
pp. 95-107
Author(s):  
Aleksandar Savic ◽  
Jozef Kratica ◽  
Vladimir Filipovic

This paper deals with the rectangle packing problem, of filling a big rectangle with smaller rectangles, while the rectangle dimensions are real numbers. A new nonlinear programming formulation is presented and the validity of the formulation is proved. In addition, two cases of the problem are presented, with and without rotation of smaller rectangles by 90?. The mixed integer piecewise linear formulation derived from the model is given, but with a simple form of the objective function.


Optimization ◽  
2012 ◽  
Vol 63 (11) ◽  
pp. 1637-1663 ◽  
Author(s):  
Armin Fügenschuh ◽  
Konstanty Junosza-Szaniawski ◽  
Zbigniew Lonc

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