关键词: 集成调度, 改进粒子群优化算法, 自动化集装箱码头, 最小化能耗

Abstract: Aiming at the integrated scheduling problem of quay crane and Artificial Intelligence Robot of Transportation (ART) in automated container terminal,the energy consumption were divided into multiple forms according to the different operation states of the equipment.An integrated scheduling model was established,which took the minimum energy consumption of quay crane and ART as optimization target.To improve the solution quality,an adaptive particles swarm optimization with recombination variation and random disturbance was proposed.According to the search requirements in different stages,the inertia weight was adjusted adaptively.In addition,the random particles were introduced to enhance the interaction ability of individuals.Combined with the iterative process,some dimensions of the optimal particle were updated indefinitely,which provided more opportunities for getting rid of local difficulties.Taking the automated container terminal in section C of Tianjin Beijiang as the research background,the numerical experiments with instances of different sizes were conducted to compare improved algorithm with the GROBI solver and other algorithms,and the effectiveness of the proposed model and algorithm were verified.The results showed that the operation process was accelerated with the gradual increase of the number of quay crane and ART,and the total energy consumption of the terminal was decreased and then increased respectively.Compared with the traditional scheduling model,the proposed method could save more energy consumption in shorter completion time.

Key words: integrated scheduling, improved particles swarm optimization, automated container terminal, minimum energy consumption