The Multi-Objective Shortest Path Problem with Multimodal Transportation for Emergency Logistics

Jinzuo Guo, Hongbin Liu, Tianyu Liu (), Guopeng Song and Bo Guo
Additional contact information
Jinzuo Guo: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Hongbin Liu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Tianyu Liu: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Guopeng Song: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Bo Guo: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Mathematics, 2024, vol. 12, issue 17, 1-21

Abstract: The optimization of emergency logistical transportation is crucial for the timely dispatch of aid and support to affected areas. By incorporating practical constraints into emergency logistics, this study establishes a multi-objective shortest path mixed-integer programming model based on a multimodal transportation network. To solve multi-objective shortest path problems with multimodal transportation, we design an ideal point method and propose a procedure for constructing the complete Pareto frontier based on the k -shortest path multi-objective algorithm. We use modified Dijkstra and Floyd multimodal transportation shortest path algorithms to build a k -shortest path multi-objective algorithm. The effectiveness of the proposed multimodal transportation shortest path algorithm is verified using empirical experiments carried out on test sets of different scales and a comparison of the runtime using a commercial solver. The results show that the modified Dijkstra algorithm has a runtime that is 100 times faster on average than the modified Floyd algorithm, which highlights its greater applicability in large-scale multimodal transportation networks, demonstrating that the proposed method both has practical significance and can generate satisfactory solutions to the multi-objective shortest path problem with multimodal transportation in the context of emergency logistics.

Keywords: emergency logistics; multimodal transportation; multi-objective shortest path; mixed-integer programming (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/17/2615/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/17/2615/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:17:p:2615-:d:1462879

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().