{"title":"用社会蜘蛛优化算法求解大规模0-1背包问题","authors":"Guo Zhou, Ruixin Zhao, Yongquan Zhou","doi":"10.1504/IJCSM.2018.10016491","DOIUrl":null,"url":null,"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.","PeriodicalId":399731,"journal":{"name":"Int. J. Comput. Sci. Math.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Solving large-scale 0-1 knapsack problem by the social-spider optimisation algorithm\",\"authors\":\"Guo Zhou, Ruixin Zhao, Yongquan Zhou\",\"doi\":\"10.1504/IJCSM.2018.10016491\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":399731,\"journal\":{\"name\":\"Int. J. Comput. Sci. Math.\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Sci. Math.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJCSM.2018.10016491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Sci. Math.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCSM.2018.10016491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solving large-scale 0-1 knapsack problem by the social-spider optimisation algorithm
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.