Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure
In this paper, we propose a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordina...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Kharazmi University
2016-11-01
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| Series: | International Journal of Supply and Operations Management |
| Subjects: | |
| Online Access: | http://ijsom.com/article_2697_500.html |
| _version_ | 1828198826730586112 |
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| author | Luca D'Acierno Antonio Placido Mariisa Botte Mariano Gallo Bruno Montella |
| author_facet | Luca D'Acierno Antonio Placido Mariisa Botte Mariano Gallo Bruno Montella |
| author_sort | Luca D'Acierno |
| collection | DOAJ |
| description | In this paper, we propose a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordinary conditions as rapidly as possible. In this context, the use of rail simulation is vital: for each intervention strategy it provides the evaluation of interactions and performance analysis prior to actually implementing the corrective action. However, in most cases, simulation tasks are deterministic and fail to allow for the stochastic distribution of train performance and delays. Hence, the strategies adopted might not be robust enough to ensure effectiveness of the intervention. We therefore propose an off-line procedure for disruption management based on a microscopic and stochastic rail simulation which considers both service operation and travel demand. An application in the case of a real metro line in Naples (Italy) shows the benefits of the proposed approach in terms of service quality. |
| first_indexed | 2024-04-12T10:44:32Z |
| format | Article |
| id | doaj.art-4f701c02aa4d4bd6af26bd162dea7125 |
| institution | Directory Open Access Journal |
| issn | 2383-1359 2383-2525 |
| language | English |
| last_indexed | 2024-04-12T10:44:32Z |
| publishDate | 2016-11-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | International Journal of Supply and Operations Management |
| spelling | doaj.art-4f701c02aa4d4bd6af26bd162dea71252022-12-22T03:36:29ZengKharazmi UniversityInternational Journal of Supply and Operations Management2383-13592383-25252016-11-013313411372Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems FailureLuca D'Acierno0Antonio Placido1Mariisa Botte2 Mariano Gallo3Bruno Montella4Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Naples, ItalyD’Appolonia S.p.A., Naples, ItalyDepartment of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Naples, ItalyDepartment of Engineering, University of Sannio, Benevento, ItalyDepartment of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Naples, ItalyIn this paper, we propose a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordinary conditions as rapidly as possible. In this context, the use of rail simulation is vital: for each intervention strategy it provides the evaluation of interactions and performance analysis prior to actually implementing the corrective action. However, in most cases, simulation tasks are deterministic and fail to allow for the stochastic distribution of train performance and delays. Hence, the strategies adopted might not be robust enough to ensure effectiveness of the intervention. We therefore propose an off-line procedure for disruption management based on a microscopic and stochastic rail simulation which considers both service operation and travel demand. An application in the case of a real metro line in Naples (Italy) shows the benefits of the proposed approach in terms of service quality.http://ijsom.com/article_2697_500.htmlSensitivity AnalysisPublic Transport ManagementRail SystemTravel Demand EstimationQuality of Service |
| spellingShingle | Luca D'Acierno Antonio Placido Mariisa Botte Mariano Gallo Bruno Montella Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure International Journal of Supply and Operations Management Sensitivity Analysis Public Transport Management Rail System Travel Demand Estimation Quality of Service |
| title | Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure |
| title_full | Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure |
| title_fullStr | Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure |
| title_full_unstemmed | Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure |
| title_short | Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure |
| title_sort | defining robust recovery solutions for preserving service quality during rail metro systems failure |
| topic | Sensitivity Analysis Public Transport Management Rail System Travel Demand Estimation Quality of Service |
| url | http://ijsom.com/article_2697_500.html |
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