{"title":"动态环境下基于贡献的多种群方法资源分配方案","authors":"Mai Peng, Changhe Li","doi":"10.1109/IAI50351.2020.9262217","DOIUrl":null,"url":null,"abstract":"The multi-population method is a common method for solving dynamic optimization problems. However, to design an efficient multi-population method, one of the challenging issues is how to allocate computational resources between populations given a limited computing buget in dynamic environments. This paper designs a contribution-based resource allocation mechanism. In this mechanism, a contribution degree of a population is defined according to the performance of the population, which determines the probability of the population to obtain the computing resource. This mechanism is implemented in an adaptive multi-population method. Experimental results on the moving peaks benchmark show that the algorithm equipped with the resource allocation mechanism outperforms the original algorithms.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Contribution-based Resource Allocation Scheme for Multi-population Methods in Dynamic Environments\",\"authors\":\"Mai Peng, Changhe Li\",\"doi\":\"10.1109/IAI50351.2020.9262217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The multi-population method is a common method for solving dynamic optimization problems. However, to design an efficient multi-population method, one of the challenging issues is how to allocate computational resources between populations given a limited computing buget in dynamic environments. This paper designs a contribution-based resource allocation mechanism. In this mechanism, a contribution degree of a population is defined according to the performance of the population, which determines the probability of the population to obtain the computing resource. This mechanism is implemented in an adaptive multi-population method. Experimental results on the moving peaks benchmark show that the algorithm equipped with the resource allocation mechanism outperforms the original algorithms.\",\"PeriodicalId\":137183,\"journal\":{\"name\":\"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)\",\"volume\":\"117 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAI50351.2020.9262217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI50351.2020.9262217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Contribution-based Resource Allocation Scheme for Multi-population Methods in Dynamic Environments
The multi-population method is a common method for solving dynamic optimization problems. However, to design an efficient multi-population method, one of the challenging issues is how to allocate computational resources between populations given a limited computing buget in dynamic environments. This paper designs a contribution-based resource allocation mechanism. In this mechanism, a contribution degree of a population is defined according to the performance of the population, which determines the probability of the population to obtain the computing resource. This mechanism is implemented in an adaptive multi-population method. Experimental results on the moving peaks benchmark show that the algorithm equipped with the resource allocation mechanism outperforms the original algorithms.