• Binod Kumar Singh

This research delves into the intricate domain of shortest route planning within road networks. Navigating through the historical foundations and contemporary challenges, the study explores classic algorithms such as Dijkstra's and Bellman-Ford, highlighting their contributions and limitations. Optimization techniques, including metaheuristic algorithms like Genetic Algorithms and Simulated Annealing, are scrutinized for their efficacy in addressing scalability issues. The evolution towards real-time route planning, fueled by GPS and live traffic data, is investigated, emphasizing adaptability to dynamic urban conditions. Machine learning's integration into route planning systems is examined, focusing on predictive modeling and reinforcement learning to enhance adaptability and self-learning capabilities. Multi-objective optimization techniques are explored as a means to balance conflicting criteria, addressing the diverse needs of users and decision-makers. The study also sheds light on emerging concerns surrounding privacy and security in route planning systems, emphasizing encryption, anonymization, and privacy-preserving algorithms. Optimizing route planning has become an indispensable component of various applications, ranging from transportation and logistics to urban planning. This article dives into the intricate world of shortest route algorithms, aiming to provide a comprehensive understanding of their foundations, applications, and the evolution of techniques employed to find the most efficient paths in road networks. With a focus on classic algorithms like Dijkstra's and Bellman-Ford, as well as modern approaches such as A* and bidirectional search, this exploration sheds light on their strengths, limitations, and the ongoing advancements that continue to shape the field.

Route Planning, Road Networks, Optimization, Real-Time Traffic, Machine Learning, Privacy, Multi-Objective Optimization

"“A Study of Shortest Route Planning In A Road Network”", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.e235-e241, February-2024, Available :http://www.jetir.org/papers/JETIR2402431.pdf

"“A Study of Shortest Route Planning In A Road Network”", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppe235-e241, February-2024, Available at : http://www.jetir.org/papers/JETIR2402431.pdf