Multimodal Transportation Route Optimization of Emergency Supplies Under Uncertain Conditions

In recent years, the frequency of sudden disaster events has increased significantly, leading to substantial and often irreparable losses for society and individuals. Although the comprehensive development of China’s transportation network has laid a solid foundation for the transportation of emergency supplies, the construction of an optimized transportation system for emergency logistics still faces considerable challenges, particularly given the uncertainties of the transportation environment. To ensure the efficient delivery of emergency supplies to disaster sites via optimal routes and the utilization of multimodal transport for logistics distribution, this paper addresses the following key objectives. First, recognizing the uncertainties in parameters such as transportation time and cost due to dynamic changes in the transportation environment as well as the limitations of transshipment capacity, we developed a multimodal transport path optimization model for emergency supplies. The model aims to minimize both transportation time and costs. Second, in addressing uncertain parameters, we employed the theory of interval number ranking, defining a risk coefficient to convert uncertain parameters into deterministic ones. This enabled a deterministic transformation of the model. Additionally, a weighted scoring method was applied to assign weights to each objective, effectively transforming the multi-objective optimization problem into a single-objective problem. Finally, we applied the genetic algorithm, particle swarm optimization algorithm, and a hybrid genetic–particle swarm algorithm to solve the model. The effectiveness of the model and the superiority of the hybrid algorithm were verified through case studies. Furthermore, a sensitivity analysis of the parameters and an investigation into the influence of the risk coefficient were conducted, providing valuable insights for relevant decision-making departments in formulating emergency material transportation plans.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-12-12
DOI
https://doi.org/10.3390/su162410905
Citations
15
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
3.05
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multimodal Transportation Route Optimization of Emergency Supplies Under Uncertain Conditions

Genghua Ma, Shukang Zheng, Zhichao Chen, Changjiang Zheng et al.
15 citations
Sustainability
Transportation and Mobility Innovations
3.05
article

Multimodal Transportation Route Optimization of Emergency Supplies Under Uncertain Conditions

Genghua Ma, Shukang Zheng, Zhichao Chen, Changjiang Zheng, Zhi Xu
article en
15 citations

Abstract

In recent years, the frequency of sudden disaster events has increased significantly, leading to substantial and often irreparable losses for society and individuals. Although the comprehensive development of China’s transportation network has laid a solid foundation for the transportation of emergency supplies, the construction of an optimized transportation system for emergency logistics still faces considerable challenges, particularly given the uncertainties of the transportation environment. To ensure the efficient delivery of emergency supplies to disaster sites via optimal routes and the utilization of multimodal transport for logistics distribution, this paper addresses the following key objectives. First, recognizing the uncertainties in parameters such as transportation time and cost due to dynamic changes in the transportation environment as well as the limitations of transshipment capacity, we developed a multimodal transport path optimization model for emergency supplies. The model aims to minimize both transportation time and costs. Second, in addressing uncertain parameters, we employed the theory of interval number ranking, defining a risk coefficient to convert uncertain parameters into deterministic ones. This enabled a deterministic transformation of the model. Additionally, a weighted scoring method was applied to assign weights to each objective, effectively transforming the multi-objective optimization problem into a single-objective problem. Finally, we applied the genetic algorithm, particle swarm optimization algorithm, and a hybrid genetic–particle swarm algorithm to solve the model. The effectiveness of the model and the superiority of the hybrid algorithm were verified through case studies. Furthermore, a sensitivity analysis of the parameters and an investigation into the influence of the risk coefficient were conducted, providing valuable insights for relevant decision-making departments in formulating emergency material transportation plans.

SustainabilityVol. 16(24)
Hohai University (CN)
Climate action
Openalex Percentile: Top 8%
Transportation and Mobility Innovations
3.05
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.