The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times
Liner shipping repositioning is the costly process of moving container ships between services in a liner shipping network to adjust the network to the changing demands of customers. Existing deterministic models for the liner shipping fleet repositioning problem (LSFRP) ignore the inherent uncertain...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-01-01
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| Series: | EURO Journal on Transportation and Logistics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2192437621000224 |
| _version_ | 1828341610877812736 |
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| author | Stefan Kuhlemann Jana Ksciuk Kevin Tierney Achim Koberstein |
| author_facet | Stefan Kuhlemann Jana Ksciuk Kevin Tierney Achim Koberstein |
| author_sort | Stefan Kuhlemann |
| collection | DOAJ |
| description | Liner shipping repositioning is the costly process of moving container ships between services in a liner shipping network to adjust the network to the changing demands of customers. Existing deterministic models for the liner shipping fleet repositioning problem (LSFRP) ignore the inherent uncertainty present in the input parameters. Assuming these parameters are deterministic could lead to extra costs when plans computed by a deterministic model are realized. We introduce an optimization model for the stochastic LSFRP that handles uncertainty regarding container demands and ship travel times. We extend existing LSFRP instances with uncertain parameters and use this new dataset to evaluate our model. We demonstrate the influence of uncertain demand and travel times on the resulting repositioning plans. Furthermore, we show that stochastic optimization generates solutions yielding up to ten times higher expected values and more robust solutions, measured against the CVaR90 objective, for decision-makers in the liner shipping industry compared to the application of deterministic optimization in the literature. |
| first_indexed | 2024-04-13T23:16:27Z |
| format | Article |
| id | doaj.art-94b3222afd694cf38cfc682861c80530 |
| institution | Directory Open Access Journal |
| issn | 2192-4384 |
| language | English |
| last_indexed | 2024-04-13T23:16:27Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EURO Journal on Transportation and Logistics |
| spelling | doaj.art-94b3222afd694cf38cfc682861c805302022-12-22T02:25:24ZengElsevierEURO Journal on Transportation and Logistics2192-43842021-01-0110100052The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel timesStefan Kuhlemann0Jana Ksciuk1Kevin Tierney2Achim Koberstein3Universität Bielefeld, Universitätsstraße 25, 33615 Bielefeld, Germany; Corresponding author.Europa-Universität Viadrina, Große Scharrnstraße 59, 15230 Frankfurt (Oder), GermanyUniversität Bielefeld, Universitätsstraße 25, 33615 Bielefeld, GermanyEuropa-Universität Viadrina, Große Scharrnstraße 59, 15230 Frankfurt (Oder), GermanyLiner shipping repositioning is the costly process of moving container ships between services in a liner shipping network to adjust the network to the changing demands of customers. Existing deterministic models for the liner shipping fleet repositioning problem (LSFRP) ignore the inherent uncertainty present in the input parameters. Assuming these parameters are deterministic could lead to extra costs when plans computed by a deterministic model are realized. We introduce an optimization model for the stochastic LSFRP that handles uncertainty regarding container demands and ship travel times. We extend existing LSFRP instances with uncertain parameters and use this new dataset to evaluate our model. We demonstrate the influence of uncertain demand and travel times on the resulting repositioning plans. Furthermore, we show that stochastic optimization generates solutions yielding up to ten times higher expected values and more robust solutions, measured against the CVaR90 objective, for decision-makers in the liner shipping industry compared to the application of deterministic optimization in the literature.http://www.sciencedirect.com/science/article/pii/S2192437621000224Liner shipping fleet repositioning problemStochastic optimization modelUncertain demandsUncertain travel times |
| spellingShingle | Stefan Kuhlemann Jana Ksciuk Kevin Tierney Achim Koberstein The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times EURO Journal on Transportation and Logistics Liner shipping fleet repositioning problem Stochastic optimization model Uncertain demands Uncertain travel times |
| title | The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times |
| title_full | The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times |
| title_fullStr | The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times |
| title_full_unstemmed | The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times |
| title_short | The stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times |
| title_sort | stochastic liner shipping fleet repositioning problem with uncertain container demands and travel times |
| topic | Liner shipping fleet repositioning problem Stochastic optimization model Uncertain demands Uncertain travel times |
| url | http://www.sciencedirect.com/science/article/pii/S2192437621000224 |
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