Solving the packing and strip-packing problems with genetic algorithms

1999 ◽  
pp. 709-718 ◽  
Author(s):  
Alberto Gomez ◽  
David de la Fuente
Keyword(s):  
Genetic Algorithms ◽  
Strip Packing ◽  
Packing Problems

Resolution of strip-packing problems with genetic algorithms

2000 ◽  
Vol 51 (11) ◽  
pp. 1289-1295 ◽  
Author(s):  
A Gómez ◽  
D de la Fuente
Keyword(s):  
Genetic Algorithms ◽  
Strip Packing ◽  
Packing Problems

Resolution of Strip-Packing Problems with Genetic Algorithms

2000 ◽  
Vol 51 (11) ◽  
pp. 1289
Author(s):  
A. Gomez ◽  
D. de la Fuente
Keyword(s):  
Genetic Algorithms ◽  
Strip Packing ◽  
Packing Problems

MINLP formulations for solving strip packing problems in LCD mother glass production

2013 ◽  
Vol 48 ◽  
pp. 312-324 ◽  
Author(s):  
Kyung Tae Park ◽  
Hansol Kim ◽  
Soobin Lee ◽  
Ho-Kyung Lee ◽  
Jun-hyung Ryu ◽  
...  
Keyword(s):  
Glass Production ◽  
Strip Packing ◽  
Packing Problems

scholarly journals A Parallel Biased Random-Key Genetic Algorithm with Multiple Populations Applied to Irregular Strip Packing Problems

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Bonfim Amaro Júnior ◽  
Plácido Rogério Pinheiro ◽  
Pedro Veras Coelho
Keyword(s):  
Genetic Algorithm ◽  
Packing Problem ◽  
Benchmark Problems ◽  
Strip Packing ◽  
Layout Problem ◽  
Multiple Populations ◽  
Packing Problems ◽  
Free Region ◽  
Positioning Method ◽  
The Given

The irregular strip packing problem (ISPP) is a class of cutting and packing problem (C&P) in which a set of items with arbitrary formats must be placed in a container with a variable length. The aim of this work is to minimize the area needed to accommodate the given demand. ISPP is present in various types of industries from manufacturers to exporters (e.g., shipbuilding, clothes, and glass). In this paper, we propose a parallel Biased Random-Key Genetic Algorithm (µ-BRKGA) with multiple populations for the ISPP by applying a collision-free region (CFR) concept as the positioning method, in order to obtain an efficient and fast layout solution. The layout problem for the proposed algorithm is represented by the placement order into the container and the corresponding orientation. In order to evaluate the proposed (µ-BRKGA) algorithm, computational tests using benchmark problems were applied, analyzed, and compared with different approaches.

A Hyper-Heuristic Approach to Strip Packing Problems

2010 ◽  
pp. 465-474 ◽  
Author(s):  
Edmund K. Burke ◽  
Qiang Guo ◽  
Graham Kendall
Keyword(s):  
Heuristic Approach ◽  
Strip Packing ◽  
Packing Problems

scholarly journals Nature inspired genetic algorithms for hard packing problems

2008 ◽  
Vol 179 (1) ◽  
pp. 393-419 ◽  
Author(s):  
Philipp Rohlfshagen ◽  
John A. Bullinaria
Keyword(s):  
Genetic Algorithms ◽  
Packing Problems

New and improved level heuristics for the rectangular strip packing and variable-sized bin packing problems

2010 ◽  
Vol 203 (2) ◽  
pp. 306-315 ◽  
Author(s):  
Frank G. Ortmann ◽  
Nthabiseng Ntene ◽  
Jan H. van Vuuren
Keyword(s):  
Bin Packing ◽  
Strip Packing ◽  
Packing Problems ◽  
Rectangular Strip
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