  The emergence of dynamic rerouting in multi-modal transportation networks has
emerged as a crucial area in operations research, revolutionizing routine
optimization. The review study analyzes multiple research publications on
algorithms and techniques related to dynamic rerouting to give a thorough
summary of the state of research in this field and provide future suggestions.
The research paper explains the importance of dynamic rerouting in modern
transportation systems and recognizes its critical role in tackling issues like
accidents, traffic congestion, and infrastructure constraints. In addition, the
review examines the development of dynamic rerouting techniques by examining
several studies to uncover the theoretical foundation, technological
developments, and effects of the practices on various forms of transportation.
The paper emphasizes the potential of technological advancements such as
artificial intelligence, the Internet of Things, and big data in transforming
routing efficiencies. Further, the review presents specific difficulties and
best practices for each mode of transportation, highlighting the many uses of
dynamic rerouting in air, sea, rail, and road transportation. The review also
digs deeper into the integration barriers common in multi-modal networks,
highlighting successful case studies that overcome these obstacles as well as
strategic approaches and regulatory modifications. Lastly, the research paper
assesses the impact of dynamic rerouting on urban development, sustainability,
and potential directions for future research such as the integration of large
language models. The comprehensive literature review incorporates multiple
research perspectives to offer significant insights into the efficacy,
challenges, and potential future pathways for dynamic rerouting within
multi-modal transportation networks.
