RESEARCH PAPER
Maintenance Tasks Scheduling in a Limited Space with Limited Resources
1
College of Intelligence Science and Technology, National University of Defense Technology, China
2
National Key Laboratory of Equipment State Sensing and Smart Support, National University of Defense Technology, China
3
China North Vehicle Research Institute, China
4
School of Mechanical Engineering, Northwestern Polytechnical University, China
A – Conceptualization; B – Methodology; C – Software; D – Validation; E – Formal analysis; F – Investigation; G – Resources; H – Data curation; I – Writing – original draft; J – Writing – review & editing; K – Visualization; L – Supervision; M – Project administration; N – Funding acquisition
Submission date: 2026-02-24
Final revision date: 2026-04-22
Acceptance date: 2026-09-21
Online publication date: 2026-10-17
Corresponding author
Jinlong Zhao
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
KEYWORDS
TOPICS
ABSTRACT
Maintenance tasks scheduling is one of the essential factors in maintenance engineering. This paper focuses on the maintenance task scheduling problem in confined spaces under resource-constrained scenarios (e.g., maintenance task planning during annual inspections in ship engine rooms or offshore drilling platforms), where spatial limitations and multi-resource availability jointly impact maintenance efficiency. Considering the constraints of different priority of maintenance tasks, unequal required area for maintenance activities and corresponding maintenance time with different resource limits, it is important to organize and schedule the maintenance activities in a way which can minimize the total maintenance duration. The problem is modelled as a mixed integer quadratic programming problem, and numerical case studies with 12 maintenance tasks are used to illustrate the optimal solutions under different scenarios and to verify the effectiveness of the proposed model. The study provides a prototype model and based on which some dynamic scheduling strategy can be proposed.
REFERENCES (36)
1.
He J, Khebbache S, Anjos MF, Hadji M. Optimization of maintenance for complex manufacturing systems using stochastic remaining useful life prognostics. Computers & Industrial Engineering 2023; 182: 109348. https://www.doi.org/10.1016/j.....
2.
Zhang Y, Ouyang L, Meng X, Zhu X.Condition-based maintenance considering imperfect inspection for a multi-state system subject to competing and hidden failures. Computers & Industrial Engineering 2024; 188: 109856. https://www.doi.org/10.1016/j.....
3.
Zhang S, Du M, Tong J, Li F. Multi-objective optimization of maintenance program in multi-unit nuclear power plant sites. Reliability Engineering & System Safety 2019; 188: 532-548. https://www.doi.org/10.1016/j.....
4.
van OB, van de CP, Basten R, Demerouti E. Predictive maintenance for industry 5.0: behavioural inquiries from a work system perspective. International Journal of Production Research 2023; 61(22): 7846-7865. https://doi.org/10.1080/002075....
5.
Alexander DA, Pandey A, Kumar SK. Mathematical models for multi-stage hybrid assembly flow-shop scheduling with preventive maintenance and release times. Computers & Industrial Engineering 2023; 186: 109716. https://doi.org/10.1016/j.cie.....
6.
Chen Z, Chen Z, Zhou D, Pan E. Joint optimization of fleet-level sequential selective maintenance and repairpersons assignment for multi-state manufacturing systems. Computers & Industrial Engineering 2023; 182: 109411. https://doi.org/10.1016/j.cie.....
7.
Chen G, He W, Tian Y, Ma K. Resource-constrained project scheduling with multiple states: Bi-objective optimization model and case study of aircraft maintenance. Computers & Industrial Engineering 2024; 191: 110169. https://doi.org/10.1016/j.cie.....
8.
Zhu X, Bei X, Chatwattanasiri N, Coit WD. Optimal system design and sequential preventive maintenance under uncertain aperiodic-changing stresses. IEEE Transactions on Reliability 2018; 67(3): 907-919. https://doi.org/10.1109/TR.201....
9.
Levitin G, Xing L, Dai Y. Optimal operation and maintenance scheduling in m-out-of-n standby systems with reusable elements. Reliability Engineering & System Safety 2021; 211: 107582. https://doi.org/10.1016/j.ress....
10.
Ali MB, Sassi M, Gossa M, Harrath Y. Simultaneous scheduling of production and maintenance tasks in the job shop. International Journal of Production Research 2011; 49(13): 3891-3918. https://doi.org/10.1080/002075....
11.
Arena M, Pasquale VD, Iannone R, Miranda S, Riemma S. A maintenance driven scheduling cockpit for integrated production and maintenance operation schedule. Advances in Manufacturing 2022; 10: 205-219. https://doi.org/10.1007/s40436....
12.
Ghorbani M, Nourelfath M, Gendreau M. A two-stage stochastic programming model for selective maintenance optimization. Reliability Engineering & System Safety 2022; 223: 108480. https://doi.org/10.1016/j.ress....
13.
Zhao X, He Z, Wu Y, Qiu Q. Joint optimization of condition-based performance control and maintenance policies for mission-critical systems. Reliability Engineering & System Safety 2022; 226: 108655. https://doi.org/10.1016/j.ress....
14.
Hadi AS, Elham MJ, Reza TM, Mehdi RB. Dynamic opportunistic maintenance grouping in a lot streaming based job-shop scheduling problem. Computers & Industrial Engineering 2023; 183: 109424. https://doi.org/10.1016/j.cie.....
15.
Brimberg J, Hurley W, Wright R. Scheduling workers in a constricted area. Naval Research Logistics 1996; 43(1): 143–149. https://doi.org/10.1002/(SICI)...<143::AID-NAV9>3.0.CO;2-B.
16.
Ecker KH. Scheduling of resource tasks. European Journal of Operational Research 1999; 115: 314–327. https://doi.org/10.1016/S0377-....
17.
Mehmet E, Rami A, Mahmoud A, Abdul RA. Workers-constrained shutdown maintenance scheduling with skills flexibility: Models and solution algorithms. Computers & Industrial Engineering 2022; 172: 108575. https://doi.org/10.1016/j.cie.....
18.
Boyer V, Vallikavungal J, Rodríguez XC, Salazar-Aguilar MA. The generalized flexible job shop scheduling problem. Computers & Industrial Engineering 2021; 160: 107542. https://doi.org/10.1016/j.cie.....
19.
Akl AM, Sawah SE, Chakrabortty RK, Turan HH. A Joint Optimization of Strategic Workforce Planning and Preventive Maintenance Scheduling: A Simulation−Optimization Approach. Reliability Engineering & System Safety 2022; 219: 108175. https://doi.org/10.1016/j.ress....
20.
Ait-Kadi D, Menye JB, Kane H. Resources assignment model in maintenance activities scheduling. International Journal of Production Research 2011; 49(22): 6677-6689. https://doi.org/10.1080/002075....
21.
Marmier F, Varnier C, Zerhouni N. Proactive, dynamic and multi-criteria scheduling of maintenance activities. International Journal of Production Research 2009; 47(8): 2185-2201. https://doi.org/10.1080/002075....
22.
Hao Q, Shen W, Xue Y, Wang S. Task network-based project dynamic scheduling and schedule coordination. Advanced Engineering Informatics 2010; 24: 417-427. https://doi.org/10.1016/j.aei.....
23.
Turan HH, Kosanoglu F, Atmis M. A multi-skilled workforce optimisation in maintenance logistics networks by multithread simulated annealing algorithms. International Journal of Production Research 2021; 59(90): 2624-2646. https://doi.org/10.1080/002075....
24.
Allahyari ZM, Azab A. Mathematical modeling and multi-start search simulated annealing for unequal-area facility layout problem. Expert Systems with Applications 2018; 91: 46–62. https://doi.org/10.1016/j.eswa....
25.
Guan C, Zhang Z, Liu S, Gong J. Multi-objective particle swarm optimization for multi-workshop facility layout problem. Journal of Manufacturing Systems 2019; 53: 32-48. https://doi.org/10.1016/j.jmsy....
26.
Luo X, Yang Y, Ge Z, Wen X, Guan F. Maintainability-based facility layout optimum design of ship cabin. International Journal of Production Research 2015; 53(3): 677-694. https://doi.org/10.1080/002075....
27.
Rinaldi M, Fera M, Bottani E, Grosse EH. Workforce scheduling incorporating worker skills and ergonomic constraints. Computers & Industrial Engineering 2022; 168: 108107. https://doi.org/10.1016/j.cie.....
28.
Rebai M, Kacem I, Adjallah KH. Earliness -tardiness minimization on a single machine to schedule preventive maintenance tasks: metaheuristic and exact methods. Journal of Intelligent Manufacturing 2012; 23: 1207–1224. https://doi.org/10.1007/s10845....
29.
Allahama H, Dalalaha D. MILP of multitask scheduling of geographically distributed maintenance tasks. International Journal of Industrial Engineering Computations 2022; 13: 119–134. https://doi.org/10.5267/j.ijie....
30.
Golpîra H, Tirkolaee EB. Stable maintenance tasks scheduling: A bi-objective robust optimization model. Computers & Industrial Engineering 2019; 137: 106007. https://doi.org/10.1016/j.cie.....
31.
Zhang Y, Li C, Su X, Cui R, Wan B. A baseline-reactive scheduling method for carrier-based aircraft maintenance tasks. Complex & Intelligent Systems 2023; 9: 367-397. https://doi.org/10.1007/s40747....
32.
Li C, Zhang Y, Su X, Wang X. An Improved Optimization Algorithm for Aeronautical Maintenance and Repair Task Scheduling Problem. Mathematics 2022; 10: 3777. https://doi.org/10.3390/math10....
33.
Cheng ETC, Gupta JND, Wang G. A review of flowshop scheduling research with setup times. Production and Operations Management 2000; 9: 262-282. https://doi.org/10.1111/j.1937....
34.
Liu D, Xu Z, Li F. A three-stage decomposition algorithm for decentralized multi-project scheduling under uncertainty. Computers & Industrial Engineering 2021; 160: 107553. https://doi.org/10.1016/j.cie.....
35.
Ji S, Luan D, Chen Z, Guo D. Integrated scheduling in automated container terminals considering AGV conflict-free routing. Transportation Letters 2021; 13(7): 501-513. https://doi.org/10.1080/194278....
36.
Monemi RN, Gelareh S. Dock assignment and truck scheduling problem; consideration of multiple scenarios with resource allocation constraints. Computers & Operations Research 2023; 151: 106074. https://doi.org/10.1016/j.cor.....
Share
RELATED ARTICLE
| 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.
