Optimizing Cold Chain Logistics with Artificial Intelligence of Things (AIoT): A Model for Reducing Operational and Transportation Costs

Optimizing Cold Chain Logistics with Artificial Intelligence of Things (AIoT): A Model for Reducing Operational and Transportation Costs

Blog Article

This paper discusses the modeling and solution of a cold chain logistics (CCL) problem using artificial intelligence of things (AIoT).The presented model aims to reduce the costs of the entire CCL network by maintaining the minimum quality of cold products distributed to customers.This study considers equipping distribution centers and trucks with IoT tools and examines the advantages of using these tools to reduce logistics costs.

Also, four algorithms based on artificial intelligence (AI), including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gray Wolf Optimizer (GWO), and Emperor Penguin Optimizer (EPO), have been used in solving the mathematical model.The analysis mitski nsfw results show that equipping trucks and distribution centers with the Internet of Things has increased the total costs by 15% compared to before.This approach resulted in a 26% reduction in operating costs and a 60% reduction in transportation costs.

As a result of using the Internet of Things, total costs have been reduced by 2.78%.Furthermore, the performance of AI algorithms hubbell 5362w showed that the high speed of these algorithms is guaranteed against the high accuracy of the obtained results.

So, EPO has achieved the optimal value of the objective function compared to a 70% reduction in the solution time.Further analyses show the effectiveness of EPO in the indicators of average objective function, average RPD error, and solution time.The results of this paper help managers understand the need to create IoT infrastructure in the distribution of cold products to customers.

Because implementing IoT devices can offset a large portion of transportation and energy costs, this paper provides management solutions and insights at the end.As a result, there is a need to deploy IoT tools in other parts of the mathematical model and its application.