Meditya Wasesa, Fakhri I. Ramadhan, Arfenia Nita, Prawira F. Belgiawan, Lidia Mayangsari
{"title":"超售预订机制对集装箱码头运营绩效及温室气体排放的影响","authors":"Meditya Wasesa, Fakhri I. Ramadhan, Arfenia Nita, Prawira F. Belgiawan, Lidia Mayangsari","doi":"10.1016/j.ajsl.2021.01.002","DOIUrl":null,"url":null,"abstract":"<div><p>Truck appointment systems facilitate coordination between container terminals and drayage trucks in container pick-up operation reservation. However, in many cases, trucks with a reservation do not arrive at the scheduled appointment. As the number of no-shows increases, the container terminal’s productivity will plummet, and drayage trucks that failed to get reservations will lose their opportunity to get service. This research proposes an overbooking reservation mechanism (ORM) to alleviate the negative impact of these no-shows. This research scrutinizes the detailed process mapping of the existing reservation mechanism, proposes an ORM, and conducts agent-based simulations to evaluate the ORM's performance against the regular and go-show reservation mechanisms at different levels of no-shows and working occupancies. The application of an ORM can improve productivity and service levels while minimizing such negative externalities as queue length, overtime, and greenhouse gas emissions. High overtime intensities only appear when the container terminal's workload is exceptionally high, at 200% of maximum capacity, with a low level of no-shows. Even in exceptionally high demand conditions, the drayage trucks wait only up to 16 min before receiving service.</p></div>","PeriodicalId":46505,"journal":{"name":"Asian Journal of Shipping and Logistics","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ajsl.2021.01.002","citationCount":"5","resultStr":"{\"title\":\"Impact of overbooking reservation mechanism on container terminal’s operational performance and greenhouse gas emissions\",\"authors\":\"Meditya Wasesa, Fakhri I. Ramadhan, Arfenia Nita, Prawira F. Belgiawan, Lidia Mayangsari\",\"doi\":\"10.1016/j.ajsl.2021.01.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Truck appointment systems facilitate coordination between container terminals and drayage trucks in container pick-up operation reservation. However, in many cases, trucks with a reservation do not arrive at the scheduled appointment. As the number of no-shows increases, the container terminal’s productivity will plummet, and drayage trucks that failed to get reservations will lose their opportunity to get service. This research proposes an overbooking reservation mechanism (ORM) to alleviate the negative impact of these no-shows. This research scrutinizes the detailed process mapping of the existing reservation mechanism, proposes an ORM, and conducts agent-based simulations to evaluate the ORM's performance against the regular and go-show reservation mechanisms at different levels of no-shows and working occupancies. The application of an ORM can improve productivity and service levels while minimizing such negative externalities as queue length, overtime, and greenhouse gas emissions. High overtime intensities only appear when the container terminal's workload is exceptionally high, at 200% of maximum capacity, with a low level of no-shows. Even in exceptionally high demand conditions, the drayage trucks wait only up to 16 min before receiving service.</p></div>\",\"PeriodicalId\":46505,\"journal\":{\"name\":\"Asian Journal of Shipping and Logistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.ajsl.2021.01.002\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Shipping and Logistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S209252122100002X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Shipping and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S209252122100002X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Impact of overbooking reservation mechanism on container terminal’s operational performance and greenhouse gas emissions
Truck appointment systems facilitate coordination between container terminals and drayage trucks in container pick-up operation reservation. However, in many cases, trucks with a reservation do not arrive at the scheduled appointment. As the number of no-shows increases, the container terminal’s productivity will plummet, and drayage trucks that failed to get reservations will lose their opportunity to get service. This research proposes an overbooking reservation mechanism (ORM) to alleviate the negative impact of these no-shows. This research scrutinizes the detailed process mapping of the existing reservation mechanism, proposes an ORM, and conducts agent-based simulations to evaluate the ORM's performance against the regular and go-show reservation mechanisms at different levels of no-shows and working occupancies. The application of an ORM can improve productivity and service levels while minimizing such negative externalities as queue length, overtime, and greenhouse gas emissions. High overtime intensities only appear when the container terminal's workload is exceptionally high, at 200% of maximum capacity, with a low level of no-shows. Even in exceptionally high demand conditions, the drayage trucks wait only up to 16 min before receiving service.