Human Resource Scheduling in Urban Rail Stations Considering Multi-Personnel Skills

Ting Zhang; Jiaming Huang; Shiyu Bu; Mingyuan Duan; Tian Lei

Abstract

The rapid development of urban rail systems and the growing number of passengers brought significant challenges to the operation of urban rail system. Scientific and reasonable human resource scheduling at urban rail stations plays a vital role in ensuring efficient operation and management of urban rail system. Traditional human resource scheduling methods often concentrated in a single station, and adopts the scheduling mode of fixed time posts, and there are some problems such as managers using the mode of experience scheduling, neglects the characteristic of operation tasks and the skill characteristics of personnel at urban rail stations. To address this problem, this study combines the reality of skill matching between employees with different levels and skills, so as to propose a multi-objective human resource scheduling model that takes into account the characteristics of multi-skill of personnel. Meanwhile, in order to be able to guide the actual production activities, three different scenarios are considered for this purpose, and the validity of the model is verified by analyzing the variables. The results indicate that by incorporating employee skill factors into the human resource scheduling of subway stations, the utilization of skills can be effectively optimized, thereby improving service quality and operational efficiency, and at the same time, the adaptability of the system to cope with different passenger demands can be enhanced, and the system has stronger resilience to interference. The outcome of the present work is significant for improving human resource utilization and operation efficiency of urban rail stations, further facilitates the promotion and sustainable development of urban rail systems.

References

1.
Petrova, T.; Grunin, A. Transport Accessibility of Urban Districts in Megapolis: Insights from Moscow. Urban Sci. 2024, 8, 36. https://doi.org/10.3390/urbansci8020036.
2.
Hou, X.; Mei, J.; Zuo, C. An overview of urban rail transit lines in the Chinese mainland in 2021. Urban Rapid Rail Transit 2022, 35, 12–16.
3.
Truong, R.; Gkountouna, O.; Pfoser, D.; et al. Towards a Better Understanding of Public Transportation Traffic: A Case Study of the Washington, DC urban rail. Urban Sci. 2018, 2, 65. https://doi.org/10.3390/urbansci2030065.
4.
Zhao, Y. Design and Implementation of Urban Rail Transit Crew Scheduling System. Ph.D. Thesis, University of Electronic Science and Technology of China, Chengdu, China, 2018.
5.
Lin, Y.; Wang, X.; Xu, R. Semi-supervised human resource scheduling based on deep presentation in the cloud. J. Wirel. Commun. Netw. 2020, 2020, 73.
6.
Rusakova, O.; Bylkov, V. Formation of need for human resources in implementation of high-speed and super high-speed railway projects. In Aviamechanical Engineering and Transport; Atlantis Press: Dordrecht, The Netherlands, 2018.
7.
Azizi, N.; Akhavan, P.; Philsoophian, M. Exploring the factors affecting sustainable human resource productivity in railway lines. Sustainability 2021, 14, 225.
8.
Shen, L.; Liu, K.; Chai, J. Research on the Mathematical Model for Optimal Scheduling of Human Resources in the Operation and Maintenance Units of a Heavy Haul Railway. Mathematics 2022, 10, 3707.
9.
Madzík, P.; Askarnia, M. The POPRAD economic and management. In Proceedings of the International Scientific Conference, New York, NY, USA, 18–20 November 2022.
10.
Nedeliaková, E.; Valla, M.; Hranický, M.P. Outline of a method for allocating railway shift workers accounting for the difficulty of work. Transp. Probl. 2022, 17, 211–224.
11.
Yao, S. Research and Implementation of Human Resource Scheduling in Mail Distribution Center. Master’s Thesis, Nanjing University, Nanjing, China, 2020.
12.
Gamboa Madeira, S.; Fernandes, C.; Paiva, T.; et al. The Impact of Different Types of Shift Work on Blood Pressure and Hypertension: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2021, 18, 6738.
13.
Xu, Z. A Simulation Research on the Configuration and Scheduling of Managers in the Emergency Sanitation of Smart City: Take Shenzhen as an Example. Master’s thesis, Huazhong University of Science and Technology, Wuhan, China, 2019.
14.
Topaloglu, S.; Ozkarahan, I. Implicit Optimal Tour Scheduling with Flexible Break Assignments. Comput. Ind. Eng. 2003, 44, 75–89.
15.
Musliu, N.; Schaerf, A.; Slany, W. Local Search for Shift Design. Eur. J. Oper. Res. 2004, 153, 51–64.
16.
Liu, S. Hierarchical Personnel Scheduling Driven by High Time-Varying Maintenance Demands in Nursing Homes. Master’s Thesis, Guangdong University of Technology, Guangzhou, China, 2021.
17.
Hung, R. Using compressed workweeks to save labour cost. Eur. J. Oper. Res. 2004, 170, 319–322.
18.
Hung, R. Single-Shift off-Day Scheduling of a Hierarchical Workforce with Variable Demands. Eur. J. Oper. Res. 1994, 78, 49–57.
19.
Hung, R. Single-shift workforce scheduling under a compressed workweek. Omega 2009, 19, 494–497.
20.
Seçkiner, S.U.; Gökçen, H.; Kurt, M. An Integer Programming Model for Hierarchical Workforce Scheduling Problem. Eur. J. Oper. Res. 2007, 183, 694–699.
21.
Feng, X.; Tang, L.; Lu, M. Research on Scheduling of Ground Service Personnel for International Airlines Based on Hierarchical Qualifications. Transp. Syst. Eng. Inf. 2019, 19, 231.
22.
Tang, L. Generation and Shift Scheduling of Ground Service Personnel for International Airlines. Master’s Thesis, Civil Aviation University of China, Tianjin, China, 2019.
23.
Lu, M.; Wang, L. Dynamic Generation Algorithm for Ground Service Personnel Scheduling Based on Shift Patterns. Transp. Syst. Eng. Inf. 2018, 18, 54.
24.
Tian, Y. Multi-Objective Multi-Skill Resource-Constrained Project Scheduling Problem with Skill Switches: Model and Evolutionary Approaches. Comput. Ind. Eng. 2022, 167, 107897.
25.
Lim, G. J. Nurse Scheduling with Lunch Break Assignments in Operating Suites. Oper. Res. Health Care 2016, 10, 35–48.
26.
Wu, X.; Wang, R.; Hu, X. Shift scheduling and roastering problem of call centers with part-time shift consideration. Syst. Eng.-Theory Pract. 2022, 42, 198–210.
27.
Su, Q.; Zhao, F. Study on the employing Algorithm for Multi-Skill Call Center. Syst. Eng.-Theory Pract. 2015, 35, 239–246.
28.
Yang, J. Optimization Design and Application of Scheduling for Multi-Skill Call Systems Based on Set Covering Algorithm. Master’s Thesis, Hunan University, Changsha, China, 2019; pp. 47–55.
29.
Dai, T.; Li, J. Shift Design in Multi-Skill Call Center with Flexible Rest Period. Comput. Eng. Appl. 2015, 19, 226–230.
30.
Akbari, M.; Zandieh, M.; Dorri, B. Scheduling Part-Time and Mixed-Skilled Workers to Maximize Employee Satisfaction. Int. J. Adv. Manuf. Technol. 2013, 64, 1017–1027.
31.
Khorshidvand, B.; Soleimani, H.; Sibdari, S. Revenue management in a multi-level multi-channel supply chain considering pricing, greening, and advertising decisions. J. Retail. Consum. Serv. 2021, 59, 102425.
32.
Naja, F.; Hamadeh, R. Nutrition amid the COVID-19 pandemic: A multi-level framework for action. Eur. J. Clin. Nutr. 2020, 74, 1117–1121.
33.
Dam, T.T.; Ta, T.A.; Mai, T. Joint chance-constrained employing optimization in multi-skill call centers. J. Comb. Optim. 2022, 44, 354–378.
34.
Zhang, G.; Jiao, Y.; Sun, J. Research the assembly line balance and multi-skilled worker assignment using hybrid optimization algorithm. Modul. Mach. Tool Autom. 2021, 2, 149–153.
35.
Zhu, L.; Lin, J.; Li, Y. Y. A decomposition-based multi-objective genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem. Knowl.-Based Syst. 2021, 225, 107099.
36.
Lin, J.; Zhu, L.; Gao, K. A genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem. Expert Syst. Appl. 2020, 140, 112915.
37.
Afshar-Nadjafi, B. Multi-skilling in scheduling problems: A review on models, methods and applications. Comput. Ind. Eng. 2021, 151, 107004.
38.
Mirataollahi olya, R.; Shayannia, S.A.; Mehdi movahedi, M. Designing a Multi-objective Human Resource Scheduling Model Using the Tabu Search Algorithm. Discret. Dyn. Nat. Soc. 2022, 2022, 5223535. https://doi.org/10.1155/2022/5223535.
39.
Marichelvam, M.K.; Geetha, M.; Tosun, Ö. An improved particle swarm optimization algorithm to solve hybrid flow shop scheduling problems with the effect of human factors—A case study. Comput. Oper. Res. 2020, 114, 104812.
40.
Ding, H.; Gu, X. Hybrid of human learning optimization algorithm and particle swarm optimization algorithm with scheduling strategies for the flexible job-shop scheduling problem. Neurocomputing 2020, 414, 313–332.
41.
Fang, H.; Zhang, W. Optimization and Application of Communication Resource Scheduling Algorithm for Urban Rail Transit Planning. Comput. Intell. Neurosci. 2022, 2022, 5608665.
42.
Kavoosi, M.; Dulebenets, M.A.; Pasha, J. Development of algorithms for effective resource scheduling among highway–rail grade crossings: A case study for the State of Florida. Energies 2020, 13, 1419.
43.
Rao, R.V.; Shah, R. BMR and BWR: Two simple metaphor-free optimization algorithms for solving real-life non-convex constrained and unconstrained problems. arXiv 2024, arXiv:2407.11149v2.
44.
Dede, T.; Sin, T.S.; Yılmaz, M.; et al. Integrated risk management in construction project: Utilizing NDSII-BMR and NDSII-BWR for time-cost-safety trade-offs. Eng. Comput. 2025, 43, 292–325.
45.
Xia, L.; Min, M. Research on Generation of Shift Patterns for Ground Service Personnel for International Airlines Based on tabu Search Algorithm. J. Electron. Inf. Technol. 2019, 41, 2715–2721.
46.
Hajibabaei, M.; Behnamian, J. Flexible job-shop scheduling problem with unrelated parallel machines and resources-dependent processing times: A tabu search algorithm. Int. J. Manag. Sci. Eng. Manag. 2021, 16, 242–253.
47.
Xie, L.; Zhang, T.; Huang, J. Hierarchical staffing study at urban rail stations. In Proceedings of the 2022 4th International Conference on Frontiers Technology of Information and Computer (ICFTIC), Qingdao, China, 2–4 December 2022.

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