An Improved Artificial Fish Swarm Algorithm to Solve the Cutting Stock Problem

被引：3
|
作者：
Cheng, Chunying [1 ]
Bao, Lanying [2 ]
机构：
[1] Inner Mongolia Univ Nationalities, Coll Comp Sci & Technol, Tongliao 028043, Peoples R China
[2] Inner Mongolia Univ Nationalities, Coll Math, Tongliao 028043, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2018 | 2018年 / 10878卷
关键词：
Artificial fish swarm algorithm; Cutting stock problem; Improved preying behavior; Improved congestion factor; Utilization rate;
D O I：
10.1007/978-3-319-92537-0_20
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In order to improve the utilization rate of sheet, an improved artificial fish swarm algorithm is proposed in this paper, which improved the preying behavior and swarming behavior, meanwhile set upper and lower limit for the Congestion factor of swarming behavior. Furthermore, the proposed algorithm is used to solve the cutting stock problem. After comparing the results of the simulation experiment with the improved particle swarm algorithm in the literature and the basic artificial fish swarm algorithm, it shows that the optimal solution obtained by the improved artificial fish swarm algorithm is better than the algorithm in the literature, thus improves the utilization rate of sheet.
引用
收藏
页码：165 / 172
页数：8
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