DocumentCode :
1841053
Title :
A Hybrid Algorithm for Solving the Optimal Layout Problem of Rectangular Pieces
Author :
Jiang, Xingbo ; Lu, Xiaoqing ; Liu, Chengcheng ; Li, Monan
Author_Institution :
Inst. of Comput. Sci. & Technol., Peking Univ., Beijing
fYear :
2008
fDate :
18-21 Nov. 2008
Firstpage :
936
Lastpage :
941
Abstract :
In this paper, a hybrid algorithm, combined the adaptive simulated annealing genetic algorithm with the improved bottom-left algorithm, is presented for the optimal layout problem of rectangle pieces which is a NP-complete problem and possesses widespread applications in the industry. Adaptive genetic algorithm is adopted to change the probabilities of crossover and mutation automatically. Simulated annealing algorithm is used to modify the individuals whose fitness value is higher than the average fitness value of the population. The presented algorithm provides with global search capability of adaptive genetic algorithm and local search capability of simulated annealing algorithm. The computation results show that the optimal layout problem of rectangular pieces can be effectively solved by the hybrid algorithm.
Keywords :
computational complexity; computational geometry; genetic algorithms; industrial engineering; probability; search problems; simulated annealing; NP-complete problem; adaptive simulated annealing genetic algorithm; bottom-left algorithm; crossover probability; fitness value; global search capability; hybrid algorithm; local search capability; mutation probability; optimal rectangular piece layout problem; Biomedical engineering; Computational modeling; Computer science; Containers; Genetic algorithms; Heuristic algorithms; Military computing; NP-complete problem; Robustness; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3398-8
Electronic_ISBN :
978-0-7695-3398-8
Type :
conf
DOI :
10.1109/ICYCS.2008.425
Filename :
4709100
Link To Document :
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