Smart Logistics Path for Cyber-Physical Systems With Internet of Things

• Published in: IEEE access Vol. 6; pp. 70808 - 70819
• Main Author: Zhang, Ning
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; ant colony algorithm; Ant colony optimization; Cloud computing; Complex systems; Convergence; CPS; Cyber-physical systems; Data processing; Data storage; genetic algorithm; Genetic algorithms; Industrial development; Information systems; Internet of Things; Logistics; Simulated annealing; simulated annealing algorithm; Transportation industry
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2879966

Logistics system is developing in the direction of intelligence. The realization of smart logistics is inseparable from the coordination of logistics operation systems and information systems. Cyber-Physical Systems (CPS) are a new intelligent complex system that integrates deep computing, control, and communication technologies, one of its main application areas is the logistics and transportation industry. Nowadays, logistics industry is developing rapidly. Based on the existing logistics system and combining the characteristics of CPS, this paper proposes a path decision method based on intelligent algorithm. Based on the CPS logistics path decision model, the Internet of Things technology and cloud platform data storage technology are introduced into the interconnection design and data processing of the equipment layer. The application effects of ant colony algorithm, simulated annealing algorithm, and genetic algorithm in logistics path optimization are analyzed in detail. By comparing the shortest transport distance and convergence speed under the three algorithm decisions, it is concluded that the ant colony algorithm has the best path optimization effect in solving the logistics path decision.