{"title":"类蚁算法的并行框架","authors":"M. Craus, Laurentiu Rudeanu","doi":"10.1109/ISPDC.2004.37","DOIUrl":null,"url":null,"abstract":"This paper describes the work of an objective framework designed to be used in the parallelization of a set of related algorithms. As a concrete application a parallel ant colony optimization algorithm (ACO) for the travelling salesman problem (TSP) is presented. The idea behind the system we are describing is to have a reusable framework for running several sequential algorithms in a parallel environment. The algorithms that the framework can be used with have several things in common: they have to run in cycles and the work should be possible to be split between several \"processing units\". The parallel framework uses the message-passing communication paradigm and is organized as a master-slave system. The ACO for TSP implemented by means of the parallel framework proves to have good performances: approximately linear speedup and low communication cost.","PeriodicalId":62714,"journal":{"name":"骈文研究","volume":"58 1","pages":"36-41"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Parallel framework for ant-like algorithms\",\"authors\":\"M. Craus, Laurentiu Rudeanu\",\"doi\":\"10.1109/ISPDC.2004.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the work of an objective framework designed to be used in the parallelization of a set of related algorithms. As a concrete application a parallel ant colony optimization algorithm (ACO) for the travelling salesman problem (TSP) is presented. The idea behind the system we are describing is to have a reusable framework for running several sequential algorithms in a parallel environment. The algorithms that the framework can be used with have several things in common: they have to run in cycles and the work should be possible to be split between several \\\"processing units\\\". The parallel framework uses the message-passing communication paradigm and is organized as a master-slave system. The ACO for TSP implemented by means of the parallel framework proves to have good performances: approximately linear speedup and low communication cost.\",\"PeriodicalId\":62714,\"journal\":{\"name\":\"骈文研究\",\"volume\":\"58 1\",\"pages\":\"36-41\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"骈文研究\",\"FirstCategoryId\":\"1092\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2004.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"骈文研究","FirstCategoryId":"1092","ListUrlMain":"https://doi.org/10.1109/ISPDC.2004.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes the work of an objective framework designed to be used in the parallelization of a set of related algorithms. As a concrete application a parallel ant colony optimization algorithm (ACO) for the travelling salesman problem (TSP) is presented. The idea behind the system we are describing is to have a reusable framework for running several sequential algorithms in a parallel environment. The algorithms that the framework can be used with have several things in common: they have to run in cycles and the work should be possible to be split between several "processing units". The parallel framework uses the message-passing communication paradigm and is organized as a master-slave system. The ACO for TSP implemented by means of the parallel framework proves to have good performances: approximately linear speedup and low communication cost.