Abstract
Nowadays, industries have to deal with an increasingly competitive environment. In this sense, the operational process optimization to increase efficiency is crucial. The industrial systems are presently leaning toward every potential means of automation for improved accuracy and superior time management. There are significant challenges in industrial logistics management: streamline operations, customer service, transportation cost, planning, and risk management. Hence in this paper, the IoT-assisted Intelligent Logistics Transportation Management Framework has been proposed in the industrial environment to design an optimized logistics plan, improve customer service, and reduce transportation cost. This paper concentrates on identifying the optimal routes for the directed autonomous vehicle, considering different vehicles' necessities, renewable generations, logistic requests, and the essential transportation system. The experimental results have been performed, and the proposed method enhances the overall performance ratio of 97.8% and customer satisfaction ratio of 98.9% and reduces the cost function ratio of 15.2%, energy consumption ratio of 11.4%, and computation time of 0.19 s compared to other existing methods.