Machine Learning Paradigm for Internet of Things Applications

9Route Optimization for Perishable Goods Transportation System

Kowsalyadevi A. K.¹*, Megala M.² and Manivannan C.³

¹Department of ECE, PSG Institute of Technology and Applied Research, Coimbatore, India

²Department of AMCS, PSG College of Technology, Coimbatore, India

³Department of Mechanical Engineering, Coimbatore Institute of Technology, Coimbatore, India

Abstract

The chapter aims to provide an optimal solution to find the most suitable routes for a fleet of vehicles performing the transportation of goods by visiting a set of market hubs. Additionally, the method concentrates to minimize the empty trips that tend to cost, vehicle usage, fuel consumption, manpower, travel time, and CO₂ emission, respectively, thereby avoiding long routes. Primarily, a clustering algorithm is used to classify the market hubs in the entire city and nearby cities based on a threshold time and distance. Subsequently, deciding the optimal group size, the supply depot, and the required number of vehicles to be transported at a particular time and distance is performed. The dynamic approach is possible for the entire region or state as the concluding procedure in distributing the perishable goods on time with the lowest of trash.

Keywords: Vehicle routing, clustering, perishable goods carrier system, shortest route

9.1 Introduction

• Logistics is not just transporting goods. The human effort involved in planning, managing, and tracking dispatches often that leads to inefficiencies, complications, ...