Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results
The different kinds of container ships with variable numberof containers arrive to porls, each container requiring single service.In this paper, an analytical approach is developed with thehelp of bulk queueing system, to analyze and to plan the berlhoccupancy depending on the number of containers i...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Zagreb, Faculty of Transport and Traffic Sciences
2006-03-01
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| Series: | Promet (Zagreb) |
| Subjects: | |
| Online Access: | http://www.fpz.unizg.hr/traffic/index.php/PROMTT/article/view/673 |
| _version_ | 1818205245314957312 |
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| author | Zoran Radimilović Saša Jovanović |
| author_facet | Zoran Radimilović Saša Jovanović |
| author_sort | Zoran Radimilović |
| collection | DOAJ |
| description | The different kinds of container ships with variable numberof containers arrive to porls, each container requiring single service.In this paper, an analytical approach is developed with thehelp of bulk queueing system, to analyze and to plan the berlhoccupancy depending on the number of containers in on boardand on shore and on the average waiting time/average servicetime ratios. The appropriate numerical results and graphs arepresented for direct determination of the berlh occupancies fordifferent number of containers.The arrivals of container ships at container terminal areusually a stochastic process. The number of berths required willdepend on the berth occupancy. In order to determine the numberof berths required, we have to know the distribution of shiparrivals and the distribution of ship service times includingpeak factors or seasonal variations. In this paper, the relationshipbetween berlh occupancy and container ship turnaroundtime at container terminal is based on bulk-arrivals and singleservice queueing models. We have assumed that the inter-arrivaltimes and service times follow appropriate probability distributionswith determined limitations. Howeve1; given resultscan be used with a high degree of confidence for first approximatesolutions and as the control of berth occupancy or wrivalof ship to berlh. |
| first_indexed | 2024-12-12T03:54:04Z |
| format | Article |
| id | doaj.art-9510add5def3492d9f65640d03ce97c9 |
| institution | Directory Open Access Journal |
| issn | 0353-5320 1848-4069 |
| language | English |
| last_indexed | 2024-12-12T03:54:04Z |
| publishDate | 2006-03-01 |
| publisher | University of Zagreb, Faculty of Transport and Traffic Sciences |
| record_format | Article |
| series | Promet (Zagreb) |
| spelling | doaj.art-9510add5def3492d9f65640d03ce97c92022-12-22T00:39:18ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692006-03-011829910310.7307/ptt.v18i2.673531Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical ResultsZoran RadimilovićSaša JovanovićThe different kinds of container ships with variable numberof containers arrive to porls, each container requiring single service.In this paper, an analytical approach is developed with thehelp of bulk queueing system, to analyze and to plan the berlhoccupancy depending on the number of containers in on boardand on shore and on the average waiting time/average servicetime ratios. The appropriate numerical results and graphs arepresented for direct determination of the berlh occupancies fordifferent number of containers.The arrivals of container ships at container terminal areusually a stochastic process. The number of berths required willdepend on the berth occupancy. In order to determine the numberof berths required, we have to know the distribution of shiparrivals and the distribution of ship service times includingpeak factors or seasonal variations. In this paper, the relationshipbetween berlh occupancy and container ship turnaroundtime at container terminal is based on bulk-arrivals and singleservice queueing models. We have assumed that the inter-arrivaltimes and service times follow appropriate probability distributionswith determined limitations. Howeve1; given resultscan be used with a high degree of confidence for first approximatesolutions and as the control of berth occupancy or wrivalof ship to berlh.http://www.fpz.unizg.hr/traffic/index.php/PROMTT/article/view/673berlh occupancycontainer shipcontainer terminalbulk queueingship turnaround time |
| spellingShingle | Zoran Radimilović Saša Jovanović Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results Promet (Zagreb) berlh occupancy container ship container terminal bulk queueing ship turnaround time |
| title | Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results |
| title_full | Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results |
| title_fullStr | Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results |
| title_full_unstemmed | Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results |
| title_short | Berth Occupancy at Container Terminals: Comparison of Analytical and Empirical Results |
| title_sort | berth occupancy at container terminals comparison of analytical and empirical results |
| topic | berlh occupancy container ship container terminal bulk queueing ship turnaround time |
| url | http://www.fpz.unizg.hr/traffic/index.php/PROMTT/article/view/673 |
| work_keys_str_mv | AT zoranradimilovic berthoccupancyatcontainerterminalscomparisonofanalyticalandempiricalresults AT sasajovanovic berthoccupancyatcontainerterminalscomparisonofanalyticalandempiricalresults |