Optimal Path Finding Algorithm for Logistic Routing Problem

• Published in: 2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) pp. 203 - 209
• Main Authors: Srinivasan, Madhura, Sireesha, K
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.09.2022
• Subjects: Ant colony optimization; Clustering; Clustering algorithms; Costs; K-Means clustering; K-Means++process; Logistic Routing Problem; Metaheuristic; Random Process; Software algorithms; Technological innovation; Transportation; Vehicle routing; Vehicle Routing Problem; Visualization
• DOI: 10.1109/ICIIET55458.2022.9967599

The Logistic Routing Problem (LRP) is a type of Vehicle Routing Problem (VRP) that is generally about the optimal set of routes for a group of vehicles to cross over to deliver to a given set of geographical locations as customers. Cost to company plays a vital role where the economy has changed the people's way of buying things and logistics development has also increased due to this. Determining an optimal solution in a VRP is NP-hard, so the solution to solve such problems is limited. Taking this as the challenge and finding an algorithm to get an optimal solution is the goal of this paper. The optimal solution here is to minimize the traveling cost and find the best route which is an important factor in terms of logistic transportation. The proposed method is to hybridize the existing Ant colony optimization. Firstly, clustering is done to divide the larger geographical area into smaller parts using K-means Algorithm. After the clusters are availed, ACO is used for Route optimization to obtain the shortest route. The models are estimated based on the distance. The design was programmed using Python Programming in Visual Studio Code as the software platform.