{"title":"一种求解多仓库车辆路径问题的多智能体深度强化学习方法","authors":"Ali Arishi, K. Krishnan","doi":"10.1080/23270012.2023.2229842","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-agent deep reinforcement learning approach for solving the multi-depot vehicle routing problem\",\"authors\":\"Ali Arishi, K. Krishnan\",\"doi\":\"10.1080/23270012.2023.2229842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":46290,\"journal\":{\"name\":\"Journal of Management Analytics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Management Analytics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1080/23270012.2023.2229842\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Management Analytics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1080/23270012.2023.2229842","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
期刊介绍:
The Journal of Management Analytics (JMA) is dedicated to advancing the theory and application of data analytics in traditional business fields. It focuses on the intersection of data analytics with key disciplines such as accounting, finance, management, marketing, production/operations management, and supply chain management. JMA is particularly interested in research that explores the interface between data analytics and these business areas. The journal welcomes studies employing a range of research methods, including empirical research, big data analytics, data science, operations research, management science, decision science, and simulation modeling.