{"title":"需求不确定条件下空箱重新定位的多场景模型","authors":"M. Di Francesco, M. Lai, P. Zuddas","doi":"10.1109/ICADLT.2013.6568466","DOIUrl":null,"url":null,"abstract":"This paper investigates the maritime repositioning of empty containers under uncertain demand. In order to consider data uncertainty, the problem is addressed by a stochastic programming approach, in which different scenarios are included in a multi-scenario optimization model and linked by non-anticipativity conditions. Numerical experiments show the benefits of multi-scenario solutions with respect to deterministic approaches, which consider only a single point forecast for each uncertain parameter.","PeriodicalId":269509,"journal":{"name":"2013 International Conference on Advanced Logistics and Transport","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A multi-scenario model for empty container repositioning under uncertain demand\",\"authors\":\"M. Di Francesco, M. Lai, P. Zuddas\",\"doi\":\"10.1109/ICADLT.2013.6568466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the maritime repositioning of empty containers under uncertain demand. In order to consider data uncertainty, the problem is addressed by a stochastic programming approach, in which different scenarios are included in a multi-scenario optimization model and linked by non-anticipativity conditions. Numerical experiments show the benefits of multi-scenario solutions with respect to deterministic approaches, which consider only a single point forecast for each uncertain parameter.\",\"PeriodicalId\":269509,\"journal\":{\"name\":\"2013 International Conference on Advanced Logistics and Transport\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Advanced Logistics and Transport\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICADLT.2013.6568466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Advanced Logistics and Transport","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICADLT.2013.6568466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A multi-scenario model for empty container repositioning under uncertain demand
This paper investigates the maritime repositioning of empty containers under uncertain demand. In order to consider data uncertainty, the problem is addressed by a stochastic programming approach, in which different scenarios are included in a multi-scenario optimization model and linked by non-anticipativity conditions. Numerical experiments show the benefits of multi-scenario solutions with respect to deterministic approaches, which consider only a single point forecast for each uncertain parameter.