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Optimizing the Cargo Flows in Multi-modal Freight Transportation Network Under Disruptions
This study develops a multi-objective optimization approach for integrated vulnerability analysis and disturbance response preparation in intermodal freight road–rail networks under the possible risk of connection disturbance. The risk and criticality of the infrastructure components are analyzed to monitor disturbances in freight transport networks efficiently. The aim of the optimization model is to find a balance between transport charges, i.e., rerouting charges, mode shift and unsupplied demand, and the freight transport system's operation efficiency. The efficiency of the transport system is classified as the portion of consumer demand transported to destination points from the specified origin over a specified time interval. The problem is conceived as a mixed-integer linear programming paradigm and is the minimal cost flow problem extension. Two methods, including an enhanced ε-constraint approach and a heuristic routing algorithm, are suggested to solve large-size instances of the problem. The verification of the suggested algorithmic system for the control of road–rail disruptions was justified utilizing simulation experiments on real-world instances of Iranian road–rail transport networks. The results illustrate the practical ramifications of the current optimization paradigm to reduce computational time and increase freight transport performance following uncertainty in the intermodal road–rail freight network.
Optimizing the Cargo Flows in Multi-modal Freight Transportation Network Under Disruptions
This study develops a multi-objective optimization approach for integrated vulnerability analysis and disturbance response preparation in intermodal freight road–rail networks under the possible risk of connection disturbance. The risk and criticality of the infrastructure components are analyzed to monitor disturbances in freight transport networks efficiently. The aim of the optimization model is to find a balance between transport charges, i.e., rerouting charges, mode shift and unsupplied demand, and the freight transport system's operation efficiency. The efficiency of the transport system is classified as the portion of consumer demand transported to destination points from the specified origin over a specified time interval. The problem is conceived as a mixed-integer linear programming paradigm and is the minimal cost flow problem extension. Two methods, including an enhanced ε-constraint approach and a heuristic routing algorithm, are suggested to solve large-size instances of the problem. The verification of the suggested algorithmic system for the control of road–rail disruptions was justified utilizing simulation experiments on real-world instances of Iranian road–rail transport networks. The results illustrate the practical ramifications of the current optimization paradigm to reduce computational time and increase freight transport performance following uncertainty in the intermodal road–rail freight network.
Optimizing the Cargo Flows in Multi-modal Freight Transportation Network Under Disruptions
Iran J Sci Technol Trans Civ Eng
Ahmady, Mahmuod (author) / Eftekhari Yeghaneh, Yones (author)
2022-02-01
20 pages
Article (Journal)
Electronic Resource
English
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