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
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;
Conference_Titel :
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/ICNC.2013.6818028
