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.