RESEARCH PAPER
A competency-driven staff assignment approach to improving employee scheduling robustness
1
Faculty of Electronics and Computer Science, Koszalin University of Technology, ul. Śniadeckich 2, 75-453 Koszalin, Poland
2
Department of Information Systems, Kielce University of Technology, Al. 1000-lecia Państwa Polskiego, 25-314 Kielce, Poland
3
Department of Materials and Production, Aalborg University, Fibigerstræde 16, 9220 Aalborg, Denmark
Publication date: 2021-03-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(1):117-131
HIGHLIGHTS
- Projects are subject to disruptions (employee absences) that influence their execution.
- Redundancy of employee competences affects the efficiency of projects driven enterprises.
- The proposed definition of robustness allows to find redundant competency frameworks.
- The considered problem is implemented in a constraint programming environment.
- The proposed approach is verified with an example of a real-life project portfolio.
KEYWORDS
ABSTRACT
Presented paper concerns the competency-driven staff assignment and scheduling approach
to the management of project portfolios subject to perturbations caused by employee absences and/or unexpected arrival of high priority jobs. Proactive strategy is considered,
which exploits the concept of employee substitutability to improve the robustness of personnel allocation in the case of occurrence of specific types of disruptions.
Solutions obtained using the model of a constraint satisfaction problem developed in this
study are validated in series quantitative and qualitative experiments. With a view to future
implementation in a Decision Support Systems dedicated to prototyping of proactive personnel allocation, a methodology employing the concept of a competency framework-based
robustness measure is proposed. Implemented in a declarative framework, the proposed
approach allows one to find a redundant competency framework robust to a given set of
disruptions.
REFERENCES (45)
1.
Akyol S.D, Baykasoğlu A. ErgoALWABP: a multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem under ergonomic risk factors. J Intell Manuf 2019; 30: 291-302, https://doi.org/10.1007/s10845....
2.
Antosz K. Maintenance - identification and analysis of the competency gap. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20(3): 484-494, https://doi.org/10.17531/ein.2....
3.
Asensio-Cuesta S, Diego-Mas JA, Canos-Daros L, Andres-Romano C. A genetic algorithm for the design of job rotation schedules considering ergonomic and Competence criteria. International Journal of Advanced Manufacturing Technology 2012; 60: 1161-1174, https://doi.org/10.1007/s00170....
4.
Baladeh AE, Zio E. A Two-Stage Stochastic Programming Model of Component Test Plan and Redundancy Allocation for System Reliability Optimization. IEEE Transactions on Reliability 2020, https://doi.org/10.1109/TR.202....
5.
Banaszak Z, Bocewicz G. Declarative Modeling for Production Order Portfolio Scheduling. Foundations of Management 2014; 6(3): 7-24, https://doi.org/10.1515/fman-2....
6.
Bänziger T, Kunz A, Wegener K. Optimizing human-robot task allocation using a simulation tool based on standardized work descriptions. J Intell Manuf 2020, https://doi.org/10.1007/s10845....
7.
Brucker P, Qu R, Burke E. Personnel Scheduling: Models and Complexity. European Journal of Operational Research 2011; 210(3): 467-473, https://doi.org/10.1016/j.ejor....
8.
Chan P, Weil G. Cyclical Staff Scheduling Using Constraint Logic Programming, in: Practice and Theory of Automated Timetabling III, Springer Berlin Heidelberg, Lecture Notes in Computer Science 2011; 2079: 159-175, https://doi.org/10.1007/3-540-....
9.
Dugelova M, Strenitzerova M. How to select appropriate human resource controlling indicators. CBU International Conference On Innovation, Technology Transfer And Education, Prague, Czech Republic 2015, https://doi.org/10.12955/cbup.....
10.
Dück V, Ionescu L, Kliewer N, Suhl L. Increasing stability of crew and aircraft schedules. Transportation Research Part C: Emerging Technologies 2012; 20(1): 47-61, https://doi.org/10.1016/j.trc.....
11.
Ehrgott M, Ryan DM. Constructing robust crew schedules with bi-criteria optimization. Journal of Multi-Criteria Decision Analysis 2002; 11(3): 139-150, https://doi.org/10.1002/mcda.3....
12.
Felberbauer T, Gutjahr WJ, Doerner KF. Stochastic project management: multiple projects with multi-skilled human resources. Journal of Scheduling 2019; 22: 271-288, https://doi.org/10.1007/s10951....
13.
Guo S, Wang X, Fu L, Liu Y. How Individual's proactive behavior helps construction sustainability: exploring the effects of project citizenship behavior on project performance. Sustainability 2019; 11(24): 6922, https://doi.org/10.3390/su1124....
14.
Hazir O, Haouari M, Erel E. Robust scheduling and robustness measures for the discrete time/cost trade-off problem. European Journal of Operational Research 2010; 207(2): 633-643, https://doi.org/10.1016/j.ejor....
15.
Ingels J, Maenhout B. Optimised buffer allocation to construct stable personnel shift rosters. Omega 2019; 82: 102-117, https://doi.org/10.1016/j.omeg....
16.
Ingels J, Maenhout B. Employee substitutability as a tool to improve the robustness in personnel scheduling. OR Spectrum 2017, https://doi.org/10.1007/s00291....
17.
Ingels J, Maenhout B. The impact of reserve duties on the robustness of a personnel shift roster: an empirical investigation. Computers & Operations Research 2015; 61: 153-169, https://doi.org/10.1016/j.cor.....
18.
Jafari H, Haleh H. Nurse scheduling problem by considering fuzzy modeling approach to treat uncertainty on nurses' preferences for working shifts and weekends off. Journal of Optimization in Industrial Engineering 2019, https://doi.org/10.22094/joie.....
19.
Jaśkowski P. Methodology for enhancing reliability of predictive project schedules in construction. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2015; 17 (3): 470-479, https://doi.org/10.17531/ein.2....
20.
Kafiabad ST, Zanjani MK, Nourelfath M. Integrated planning of operations and on-job training in maintenance logistics networks. Reliability Engineering and System Safety 2020; 199, https://doi.org/10.1016/j.ress....
21.
Klimek M, Łebkowski P. Robustness of schedules for project scheduling problem with cash flow optimisation. Bulletin of the Polish Academy of Sciences. Technical Sciences 2013; 61(4): 1005-1015, https://doi.org/10.2478/bpasts....
22.
Korytkowski P. Competencies-based performance model of multi-skilled workers with learning and forgetting. Expert Systems With Applications 2017; 77: 226-235, https://doi.org/10.1016/j.eswa....
23.
Lecuona JR, Reitzig M. Knowledge worth having in 'excess': The value of tacit and firm-specific human resource slack. Strategic Management Journal 2014; 35(7): 954-973, https://doi.org/10.1002/smj.21....
24.
Lim K, Zheng P, Chen Ch-H. A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspective. Journal of Intelligent Manufacturing 2020; 31: 1313-1337, https://doi.org/10.1007/s10845....
25.
Liu Y, Huang HZ, Wang Z, Li YF, Zhang XL. Joint optimization of redundancy and maintenance staff allocation for multi-state seriesparallel systems. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2012; 14 (4): 312-318.
26.
Liu Y, Huang HZ, Wang Z, Li Y, Yang Y. A Joint Redundancy and Imperfect Maintenance Strategy Optimization for Multi-State Systems. IEEE Transactions on Reliability 2013; 62(2): 368-378, https://doi.org/10.1109/TR.201....
27.
Moudani W, Mora-Camino F. Solving crew reserve in airlines using dynamic programming approach. International Journal of Optimization: Theory, Methods and Applications 2010; 2(4): 302-329.
28.
Nielsen I, Wójcik R, Bocewicz G, Banaszak Z. Towards constraint programming driven methodology for online multi-project planning and control. Information Systems Architecture and Technology, Wroclaw: Wroclaw University of Technology 2014: 65-74.
29.
Niknafs A, Denzinger J, Ruhe G. A Systematic Literature Review of the Personnel Assignment Problem. Proc. of the International Multi-Conference of Engineers and Computer Scientists 2013 Vol II, MECS 2013, Hong Kong, 1121-1128, ISSN: 2078-0966.
30.
Patalas-Maliszewska J. Assessing the impact of ERP implementation in the small enterprises. Foundations of Management 2012; 4(2): 51-62, https://doi.org/10.2478/fman-2....
31.
Pawar US, Hanchate DB. Literature review on personnel scheduling. International Journal of Computer Engineering & Technology 2013; 4(5), 312-324.
32.
Pinedo ML. Planning and Scheduling in Manufacturing and Services. In: Springer Series in Operations Research, Eds.: Peter W. Glynn Stephen M. Robinson, Springer Science Business Media, Inc., New York, 2005, ISBN 0-387-22198-0.
33.
Roblek M, Majec M, Benjamin U. Knowledge-based assignment model for allocation of employees in engineering-to-order production In: Knowledge Management Strategies and Applications, Muhammad Mohiuddin, Norrin Halilem, SM Ahasanul Kobir and Cao Yuliang, IntechOpen, 2017, https://doi.org/10.5772/intech....
34.
Rocha M, Oliveira F, Carravilla M. Cyclic staff scheduling: optimization models for some real-life problems, Journal of scheduling 2013; 16(2): 231-242, https://doi.org/10.1007/s10951....
35.
Rosenberger J, Schaefer A, Goldsman D, Johnson E, Kleywegt A, Nemhauser G. A stochastic model of airline operations. Transportation Science 2002; 36(4): 357-377, https://doi.org/10.1287/trsc.3....
36.
Samson S, Reneke J A, Wiecek MM. A review of different perspectives on uncertainty and risk and alternative modelling paradigm. Reliability Engineering and System Safety 2009; 94(2): 558-567, https://doi.org/10.1016/j.ress....
37.
Supian S, Wahyuni S, Subiyanto J. Optimization of Personnel Assignment Problem Based on Traveling Time by Using Hungarian Methods: Case Study on the Central Post Office Bandung. 4th International Conference on Operational Research, IOP Conf. Series: Materials Science and Engineering 300 (2017), https://doi.org/10.1088/1757-8....
38.
Szwarc E, Bocewicz G, Banaszak Z, Wikarek J. Competence allocation planning robust to unexpected staff absenteeism. Eksploatacja i Niezawdonosc - Maintenance and Reliability 2019; 21(3): 440-450, https://doi.org/10.17531/ein.2....
39.
Szwarc E, Bocewicz G, Bach-Dąbrowska I. Planning of teacher staff competence structure robust to unexpected personnel absence. IFACPaperOnLine 2019; 52 (13): 2740-2745, https://doi.org/10.1016/j.ifac....
40.
Topaloglu S, Selim H. Nurse scheduling using fuzzy modelling approach. Fuzzy Sets and Systems 2010; 161(11): 1543-1563, https://doi.org/10.1016/j.fss.....
41.
Yun-Chia L, Smith AE. An ant colony optimization algorithm for the redundancy allocation problem (RAP). IEEE Transactions on Reliability 2004; 53(3): 417-423, https://doi.org/10.1109/TR.200....
42.
Van den Bergh J, Beliën J, De Bruecker P, Demeulemeester E, Boeck L. Personnel scheduling: a literature review. European Journal of Operational Research 2013; 226: 367-385, https://doi.org/10.1016/j.ejor....
43.
Volk R. Proactive-reactive, robust scheduling and capacity planning of deconstruction projects under uncertainty. Ph.D. Dissertation, Karlsruher Institut für Technologie, Fakultät für Wirtschaftswissenschaften, KIT Scientific Publishing, Karlsruhe, 2017.
44.
Wikarek J, Sitek P. A Data-Driven Approach to modelling and Solving Academic Teachers' Competencies Configuration Problem. Intelligent Information and Database Systems 2019, https://doi.org/10.1007/978-3-....
45.
Woodruffe C. What is meant by competency? In: Boam R., Sparrow P. (Eds.), Designing and achieving competency. New York, 1992.
CITATIONS (9):
2.
Preventive maintenance scheduling of a multi-skilled human resource-constrained project’s portfolio
G. Bocewicz, P. Golińska-Dawson, E. Szwarc, Z. Banaszak
Engineering Applications of Artificial Intelligence
G. Bocewicz, P. Golińska-Dawson, E. Szwarc, Z. Banaszak
Engineering Applications of Artificial Intelligence
3.
Proactive Operations Management: Staff Allocation with Competence Maintenance Constraints
Eryk Szwarc, Grzegorz Bocewicz, Paulina Golińska-Dawson, Zbigniew Banaszak
Sustainability
Eryk Szwarc, Grzegorz Bocewicz, Paulina Golińska-Dawson, Zbigniew Banaszak
Sustainability
4.
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference
Mariusz Piechowski, Artur Meller
Mariusz Piechowski, Artur Meller
5.
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference
Eryk Szwarc, Paulina Golińska-Dawson, Grzegorz Bocewicz, Zbigniew Banaszak
Eryk Szwarc, Paulina Golińska-Dawson, Grzegorz Bocewicz, Zbigniew Banaszak
6.
Robust Scheduling of Multi-Skilled Workforce Allocation: Job Rotation Approach
Eryk Szwarc, Paulina Golińska-Dawson, Grzegorz Bocewicz, Zbigniew Banaszak
Electronics
Eryk Szwarc, Paulina Golińska-Dawson, Grzegorz Bocewicz, Zbigniew Banaszak
Electronics
7.
Study on Operator Assignment Considering Operator Absence in Cellular Manufacturing System
Y. Yoshida, H. Haraguchi
2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
Y. Yoshida, H. Haraguchi
2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
8.
Workforce scheduling approaches for supporting human-centered algorithmic management in manufacturing: A systematic literature review and a conceptual optimization model
Florens L. Burgert, Matthäus Windhausen, Maximilian Kehder, Niklas Steireif, Susanne Mütze-Niewöhner, Verena Nitsch
Procedia Computer Science
Florens L. Burgert, Matthäus Windhausen, Maximilian Kehder, Niklas Steireif, Susanne Mütze-Niewöhner, Verena Nitsch
Procedia Computer Science
9.
Scheduling Optimization Study of Intelligent Mixing Algorithm for People in Public Places Based on Cross-Infection Risk Consideration
Kailun Li
2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT)
Kailun Li
2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT)
| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
