DocumentCode
2136142
Title
An improved Artificial Fish Swarm Algorithm for cutting stock problem
Author
Chuyi Song ; Siqin Bai ; Jingqing Jiang ; Lanying Bao
Author_Institution
Coll. of Math., Inner Mongolia Univ. for Nat., Tongliao, China
fYear
2013
fDate
23-25 July 2013
Firstpage
501
Lastpage
505
Abstract
This paper proposes an improved Artificial Fish Swarm Algorithm (AFSA) to deal with the two-dimensional non-guillotine cutting sock problem. The visual field enlarges gradually according to the iteration. A similar Bottom Left algorithm is used to map the cutting pattern to the actual layout. The simulation results show that the AFSA with an improved visual field performs better than AFSA on several test problems.
Keywords
bin packing; computational complexity; evolutionary computation; AFSA; artificial fish swarm algorithm; bottom left algorithm; cutting pattern; two-dimensional nonguillotine cutting stock problem; visual field; Approximation algorithms; Classification algorithms; Computer science; Educational institutions; Marine animals; Optimization; Visualization; artificial fish swarm algorithm; cutting stock problem; visual field;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location
Shenyang
Type
conf
DOI
10.1109/ICNC.2013.6818028
Filename
6818028
Link To Document