{"title":"将并行计算应用于粒子群优化算法中，用于解决作业车间调度问题","authors":"J. Zelenka","doi":"10.1109/INES.2011.5954742","DOIUrl":null,"url":null,"abstract":"Currently, on optimization processes requirements focusing on several parameters are emphasized. Algorithms allowing to find an optimal (near-optimal) solution, are in most cases moving in the large area of possible solutions. Their running requires strong computational support and hunger solution programs to run on multi-core workstation, clusters, grid and clouds. In this article serial and parallel computing of the Job-Shop scheduling problem by using MATLAB distributed computing server is compared.","PeriodicalId":414812,"journal":{"name":"2011 15th IEEE International Conference on Intelligent Engineering Systems","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parallel computing application into the particle swarm optimization algorithm used to solve the Job-Shop scheduling problem\",\"authors\":\"J. Zelenka\",\"doi\":\"10.1109/INES.2011.5954742\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, on optimization processes requirements focusing on several parameters are emphasized. Algorithms allowing to find an optimal (near-optimal) solution, are in most cases moving in the large area of possible solutions. Their running requires strong computational support and hunger solution programs to run on multi-core workstation, clusters, grid and clouds. In this article serial and parallel computing of the Job-Shop scheduling problem by using MATLAB distributed computing server is compared.\",\"PeriodicalId\":414812,\"journal\":{\"name\":\"2011 15th IEEE International Conference on Intelligent Engineering Systems\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 15th IEEE International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.2011.5954742\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 15th IEEE International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.2011.5954742","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel computing application into the particle swarm optimization algorithm used to solve the Job-Shop scheduling problem
Currently, on optimization processes requirements focusing on several parameters are emphasized. Algorithms allowing to find an optimal (near-optimal) solution, are in most cases moving in the large area of possible solutions. Their running requires strong computational support and hunger solution programs to run on multi-core workstation, clusters, grid and clouds. In this article serial and parallel computing of the Job-Shop scheduling problem by using MATLAB distributed computing server is compared.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
