Abstract

The objective of this paper is to find solution to the dynamic vehicle traffic routing which substantially differs from the classical vehicle routing problem in the sense of constraints and area of application. Dynamic vehicle routing address the problem of finding the least time consumable path considering change in traffic condition dynamically in our day to day traffic. Due to the complex nature of the problem, it cannot be solved exactly using traditional algorithms e.g. shortest route finding algorithms etc. In our implementation, traffic density is calculated, which is a measure of traffic, and then most feasible route is evaluated with parameters like distance, time and traffic density. Ant Colony Optimization and Genetic Algorithms have been exploited and modified to allow the search for multiple routes and to find true or approximate solution. We have also shown their comparative analysis for their fitment into real word situations and the same has been justified using supported simulation results.

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