Feiteng Zhao

In U-shaped automated container terminals (U-shaped ACTs), automated guided vehicles (AGVs) need to frequently interact with yard cranes (YCs), and separate scheduling of the two devices will affect terminal efficiency. Therefore, this study explores the coordinated scheduling problem between the two devices. To solve this problem, a high-precision simulation model of the U-shaped ACTs is established, which incorporates real operational logic. Second, an Improved Non-dominated Sorting Genetic Algorithm II based on Proximal Policy Optimization (INSGAII-PPO) is proposed. The algorithm uses PPO to realize dynamic genetic operator selection and makes related improvements, which improve the multi-objective optimization ability of NSGAII, and solve the collaborative scheduling problem by combining simulation. Finally, a hybrid weighted Technique for Order Preference by Similarity to Ideal Solution with preferences is proposed to select the final solution. The experimental results show that the scheme obtained by INSGAII-PPO exhibits better convergence and diversity, and offers significant advantages compared with the comparison algorithms. Moreover, the energy consumption and waiting time of the final solution selected by the proposed method are reduced by 3.42% and 4.87% on average. The proposed method has the capability of providing a theoretical reference for the AGVs and YCs collaborative scheduling of U-shaped ACTs.

Background: Patients with obstructive sleep apnea syndrome (OSAS) have cognitive dysfunction in many aspects, however, these patients’ decision-making function remains unclear. In this study, the Game of Dice Task (GDT) was used to investigate the function of decision making in patients with OSAS. Methods: 30 participants with moderate to severe OSAS and 27 participants with no or mild OSAS diagnosed by sleep breathing monitor were selected from June 2021 to March 2022. Risky decision making was tested through the GDT with known risk probability. General demographic information and background cognitive functions, such as the overall cognitive functioning and executive functioning, were tested to establish baseline data. Results: There were no significant differences in gender, age, and years of education between the two groups. During the GDT, the moderate to severe OSAS group opted for the safety option at a statistically significant lower rate when compared to the no or mild OSAS group (7.53 ± 4.43 vs. 10.26 ± 4.26, p = 0.022). The moderate to severe OSAS group utilized the higher risk option than the group with no or mild OSAS (10.47 ± 4.43 vs. 7.74 ± 4.26, p = 0.022). The utilization rate of negative feedback in the moderate and severe OSAS group was lower than that in the no or mild OSAS group (7.50, 52.50 vs. 28.57, 100.00, p = 0.001). At the end of the GDT, the moderate and severe OSAS group was more likely to have negative total assets than the patients with no or mild OSAS (−1846.67 ± 2587.20 vs. 300.00 ± 1509.97, p < 0.001). Multiple linear regression analysis shows that there is a negative correlation between the selection of risk options and negative feedback utilization in the GDT. Conclusion: Patients with moderate and severe OSAS displayed impaired decision-making throughout the study. Impaired decision-making is related to executive processes and may be caused by diminished prefrontal cortex functioning. However, the functions of memory, attention, language, abstraction, and orientation are relatively retained.