Application of hybrid GA-PSO based on intelligent control fuzzy system in the integrated scheduling in automated container terminal

• Published in: Journal of intelligent & fuzzy systems Vol. 39; no. 2; pp. 1525 - 1538
• Main Authors: Zhong, Meisu, Yang, Yongsheng, Zhou, Yamin, Postolache, Octavian
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2020; Sage Publications Ltd
• Subjects: Adaptive algorithms; Algorithms; Automated guided vehicles; Automation; Containers; Emissions control; Energy conservation; Energy consumption; Fuzzy control; Gantry cranes; Hybrid systems; Integer programming; Mixed integer; Scheduling; Ship terminals; intelligent control fuzzy system; intelligent optimization; Automated container terminal; loading and unloading operation
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-179926

With the development of the large ship, automated container terminals (ACTs) have serious energy consumption and carbon emission problems, reducing the loading and unloading time of ships can ease energy consumption, improve the working efficiency and service level of automated terminals. This paper studies the integrated scheduling problem of the gantry cranes (QCs), automated guided vehicles (AGVs) and automated rail-mounted gantry (ARMG) in automated terminal. According to the loading and unloading operation mode, we build the mixed integer programming model with the goal of minimizing the ship loading and unloading time, and through various algorithms of heuristic and hybrid improved to solve this problem, it proves the effectiveness of the model to obtain optimized scheduling scheme by numerical experiments, and comparing the different performance of algorithms, the results show that the hybrid GA-PSO algorithm with adaptive auto tuning is superior to other algorithms in terms of solution time and quality, which can effectively solve the problem of integrated scheduling to save the energy of automated container terminal.