Solving large-scale 0-1 knapsack problem by the social-spider optimisation algorithm

被引:19
|
作者
Zhou, Guo [1 ]
Zhao, Ruixin [2 ]
Zhou, Yongquan [2 ]
机构
[1] China Univ Polit Sci & Law, Dept Sci & Technol Teaching, Beijing 100088, Peoples R China
[2] Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Peoples R China
基金
美国国家科学基金会;
关键词
large-scale 0-1 knapsack problems; cooperative behaviour; social-spider optimisation algorithm;
D O I
10.1504/IJCSM.2018.095497
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper uses the social-spider optimisation (SSO) algorithm to solve large-scale 0-1 knapsack problems. The SSO algorithm is based on the simulation of cooperative behaviour of social-spiders. In SSO algorithm, individuals emulate a group of spiders which interact to each other based on the biological laws of the cooperative colony. The algorithm considers two different search agents (spiders): males and females. Depending on gender, each individual is conducted by a set of different evolutionary operators which mimic different cooperative behaviour which are typically found in the colony. The experiment results show that the social-spider optimisation algorithm can be an efficient alternative for large-scale 0-1 knapsack problems.
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页码:433 / 441
页数:9
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