  The proper planning of different types of public transportation such as
metro, highway, waterways, and so on, can increase the efficiency, reduce the
congestion and improve the safety of the country. There are certain challenges
associated with route planning, such as high cost of implementation, need for
adequate resource & infrastructure and resistance to change. The goal of this
research is to examine the working, applications, complexity factors,
advantages & disadvantages of Floyd- Warshall, Bellman-Ford, Johnson, Ant
Colony Optimization (ACO), Particle Swarm Optimization (PSO), & Grey Wolf
Optimizer (GWO), to find the best choice for the above application. In this
paper, comparative analysis of above-mentioned algorithms is presented. The
Floyd-Warshall method and ACO algorithm are chosen based on the comparisons.
Also, a combination of modified Floyd-Warshall with ACO algorithm is proposed.
The proposed algorithm showed better results with less time complexity, when
applied on randomly structured points within a boundary called quasi-structured
points. In addition, this paper also discusses the future works of integrating
Floyd-Warshall with ACO to develop a real-time model for overcoming above
mentioned-challenges during transportation route planning.
