Scheduling Multi-Skilled Inspectors Using the Cuckoo Optimization Algorithm: Skill–Task Matching, Workload Balancing, and Schedule Efficiency
Abstract
Scheduling multi-skilled inspectors is an NP-hard problem in technical inspection operations. This study evaluates the Cuckoo Optimization Algorithm (COA), a population-based metaheuristic, as a solution approach for this scheduling problem. Its performance is benchmarked against that of the Greedy Randomized Adaptive Search Procedure (GRASP) using a real-world case from a technical inspection company in Tunisia. In the computational comparison, COA produced higher-quality schedules than GRASP for the case examined. These findings support the use of COA for scheduling multi-skilled inspectors in technical inspection operations.
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Al-Rawi O, and Mukherjee T, 2019. Application of linear programming in optimizing labour scheduling. J Math Finance, 09(03): 272–285. https://doi.org/10.4236/jmf.2019.93016
Bowden Z, and Ragsdale C, 2018. The truck driver scheduling problem with fatigue monitoring. Decis Support Syst, 110: 20–31. https://doi.org/10.1016/j.dss.2018.03.002
Brown C, Liebovitch L, and Glendon R, 2007. Lévy flights in Dobe Ju/hoansi foraging patterns. Human Ecol, 35:129–138.
Bürgy R, Michon-Lacaze H, and Desaulniers G, 2019. Employee scheduling with short demand perturbations and extensible shifts. Omega (United Kingdom), 89: 177–192. https://doi.org/10.1016/j. omega.2018.10.009
Chaker B, Mohamed HA, and Diala D, 2019. A Framework for Multi-Skills Inspectors Scheduling with Client Preferences in Service Industry: Real Case. In International Colloquium on Logistics and Supply Chain Management, LOGISTIQUA 2019.
Chaker B, Mohamed H A, and Diala D, 2024. Multi-objective personnel scheduling problem with multiple qualifcation and client’s satisfaction: real case. Flexible Services and Manufacturing Journal. DOI:10.1007/s10696-024-09570-w
Chen R, Liang C, Gu D, and Zhao H, 2020. A competence-time-quality scheduling model of multi-skilled staf for IT project portfolio. Comput Ind Eng,139:106-183. https://doi.org/10.1016/j.cie.2019. 106183
Ciancio C, Laganà D, Musmanno R, and Santoro F, 2018. An integrated algorithm for shift scheduling problems for local public transport companies. Omega (United Kingdom), 75:1339–1351. https://doi. org/10.1016/j.omega.2017.02.007
Denkena B, Dittrich M, and Winter F, 2017. Competence-based personnel scheduling through production data. Proced CIRP, 63:265–270. https://doi.org/10.1016/j.procir.2017.03.114
Hassani R, Desaulniers G, and Elhallaoui I, 2020. Real-time personnel re-scheduling after a minor disruption in the retail industry. Comput Oper Res, p120. https://doi.org/10.1016/j.cor.2020.104952
Henao C, Muñoz J, and Ferrer J, 2019. Multiskilled workforce management by utilizing closed chains under uncertain demand: a retail industry case. Comput Ind Eng, 127:74–88. https://doi.org/10. 1016/j.cie.2018.11.061
Lobna et al. The Cuckoo Optimization Algorithm to Resolve a Multi-Skills Inspectors
19
Hochdörfer J, Hedler M, and Lanza G, 2018. Staf scheduling in job rotation environments considering ergonomic aspects and preservation of qualifcations. J Manuf Syst, 46:103–114. https://doi.org/10. 1016/j.jmsy.2017.11.005
Janacek J, Kohani M, Koniorczyk M, and Marton P, 2017. Optimization of periodic crew schedules with application of column generation method. Transp Res Part C Emerg Technol, 83 : 165–178. https:// doi.org/10.1016/j.trc.2017.07.008
Joshi A S, Kulkarni O, Kakandikar G M, and Nandedkar V M, 2017. Cuckoo Search Optimization- A Review. Materials Today: Proceedings, 4(8):7262–7269. doi:10.1016/j. matpr.2017.07.055
Koubaa M, Mohamed HA and Beji N, 2022. Solving A Real Case Of Seafaring Staff Scheduling Problem Using Cuckoo Optimization Algorithm. International Journal Of Applied Metaheuristic Computing (IJAMC), (13(1)), p 19. DOI:10.4018/IJAMC.298316
Koubaa M, Elloumi S, and Dhouib S, 2016. Optimising case study personnel scheduling problem using an artifcial bee colony algorithm. Int J Shipp Transp Logist , 8(5): 552–567.
https://doi.org/10.1504/ IJSTL.2016.10000187
Mac-Vicar M, Ferrer J, Muñoz J, and Henao C, 2017. Real-time recovering strategies on personnel scheduling in the retail industry. Comput Ind Eng, 113:589–601. https://doi.org/10. 1016/j.cie.2017.09.045
Pavlyukevich I, 2007. Lévy flights, non-local search and simulated annealing. J Comput Phys, 226:1830–1844.
Payne R, Sorenson M, and Klitz K, 2005. The Cuckoos. Oxford University Press, New York.
Rama S, Srividya S, and Bellatti D, 2017. A linear programming approach for optimal scheduling of workers in a transport corporation. Int J Eng Trends Technolo, 45(10):482–487. https://doi.org/10.14445/ 22315381/IJETT-V45P291
Shiau JY, Huang MK, and Huang CY, 2020. A hybrid personnel scheduling model for staf rostering problems. Mathematics, 8(10):1–20. https://doi.org/10.3390/math8101702
Wongwien T, and Nanthavanij S, 2017. Priority-based ergonomic workforce scheduling for industrial workers performing hazardous jobs. J Ind Prod Eng, 34(1): 52–60. https://doi.org/10.1080/21681015. 2016.1192567
Yang X S, and Deb S, 2009. Cuckoo search via Lévy flights. In: Proceedings of World Congress on Nature & Biologically Inspired Computing. IEEE Publications, USA,pp: 210–214