The uneven distribution of taskload, is a key feature for modern dispatching system as the automation can function well in most of the times while human operators must deal with a sharp increase of taskload in emergent situations. Given this, workload management skills is important for the work effectiveness of dispatchers. However, such an ability differs across different dispatchers and this difference can have an impact on the system as a whole. This study aims to investigate the differences in the performance of individual factors on workload perception and load management strategies to provide a scientific basis for ensuring the smooth operation of the HSR system. This study used a 2×2 within-subjects experimental design to conduct a workload control experiment in a laboratory setting with 32 in-service high-speed rail dispatchers of the Chengdu Railway Bureau. At the same time, basic individual information of the dispatchers was collected, including age, education, years of dispatching work tenure (dispatching tenure) and skill level. The focus was on examining the influencing factors of the peak-end effect of workload at the individual level. The results of statistical analysis show that the dispatchers with the longest or shortest dispatching tenure experienced lower mental workload in peak times, and dispatchers with higher skill levels reflected stronger work homeostasis in the peak effects; while the end effects did not show significant correlations with any of the individual-level factors examined. Based on the results of this study, we conclude that higher-skilled dispatchers have stronger work homeostasis and are able to implement "peak cutting and valley filling"workload management strategies more effectively to keep workloads within reasonable ranges in the long term. The end effect may be more similar to a generalized memory effect, which is not significantly affected by individual differences. This study provides empirical evidence to understand the individual differences in workload management of high-speed rail dispatchers, which has important practical implications for the selection, training, and job design of high-speed rail dispatchers. Future research could further explore the potential factors affecting the end effect and how these findings can be used to optimize the human-computer interaction design of the HSR dispatching system.