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

Guo Zhou, Ruixin Zhao, Yongquan Zhou
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引用次数: 15

Abstract

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.
用社会蜘蛛优化算法求解大规模0-1背包问题
本文采用社会性蜘蛛优化算法求解大规模的0-1背包问题。SSO算法基于对社会性蜘蛛合作行为的模拟。在单点登录算法中,个体模仿一组蜘蛛,这些蜘蛛根据合作群体的生物规律相互作用。该算法考虑两种不同的搜索代理(蜘蛛):雄性和雌性。根据性别的不同,每个个体都由一组不同的进化操作员来管理,这些操作员模仿群体中典型的不同合作行为。实验结果表明,社会蜘蛛优化算法可以有效地解决大规模0-1背包问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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