Design a Smart and Intelligent Routing Network Using Optimization Techniques

Abstract

The Routing Problem (RP) is designed to find the minimal set of routes in order to deliver the services to a set of customers. There are many techniques available to solve RP problems such as Ant Colony Optimization (ACO), Honey Bee Optimization (HBO), Particle Swarm Intelligence, Genetic Algorithm (GA) and much more. Our aim is to consider the various RP techniques and compare the performance of each technique based on various parameters. To carry out this, we have considered the School Bus Routing Problem (SBRP), which ensures the on-time delivery of students to and from school by minimizing the total travel cost in terms of time and distance. The result of this research work helps to determine the best RP algorithm not only based on shortest path but also additional parameters such as pheromone level, optimum path level and distance.