IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i11p1807-d823640.html
   My bibliography  Save this article

Multi-Objective Model and Variable Neighborhood Search Algorithms for the Joint Maintenance Scheduling and Workforce Routing Problem

Author

Listed:
  • Lamiaa Dahite

    (SI2M, Laboratoire Systèmes d’Information, Systèmes Intelligents et Modélisation Mathématique, Institut National de Statistique et d’Economie Appliqué, Rabat 10100, Morocco
    LISIC—UR 4491, Laboratoire d’Informatique, Signal et Image de la Côte d’Opale, Université du Littoral Côte d’Opale, 62228 Calais, France)

  • Abdeslam Kadrani

    (SI2M, Laboratoire Systèmes d’Information, Systèmes Intelligents et Modélisation Mathématique, Institut National de Statistique et d’Economie Appliqué, Rabat 10100, Morocco)

  • Rachid Benmansour

    (SI2M, Laboratoire Systèmes d’Information, Systèmes Intelligents et Modélisation Mathématique, Institut National de Statistique et d’Economie Appliqué, Rabat 10100, Morocco)

  • Rym Nesrine Guibadj

    (LISIC—UR 4491, Laboratoire d’Informatique, Signal et Image de la Côte d’Opale, Université du Littoral Côte d’Opale, 62228 Calais, France)

  • Cyril Fonlupt

    (LISIC—UR 4491, Laboratoire d’Informatique, Signal et Image de la Côte d’Opale, Université du Littoral Côte d’Opale, 62228 Calais, France)

Abstract

This paper addresses a problem faced by maintenance service providers: performing maintenance activities at the right time on geographically distributed machines subjected to random failures. This problem requires determining for each technician the sequence of maintenance operations to perform to minimize the total expected costs while ensuring a high level of machine availability. To date, research in this area has dealt with routing and maintenance schedules separately. This study aims to determine the optimal maintenance and routing plan simultaneously. A new bi-objective mathematical model that integrates both routing and maintenance considerations is proposed for time-based preventive maintenance. The first objective is to minimize the travel cost related to technicians’ routing. The second objective can either minimize the total preventive and corrective maintenance cost or the failure cost. New general variable neighborhood search (GVNS) and variable neighborhood descent (VND) algorithms based on the Pareto dominance concept are proposed and performed over newly generated instances. The efficiency of our approach is demonstrated through several experiments. Compared to the commercial solver and existing multi-objective VND and GVNS, these new algorithms obtain highly competitive results on both mono-objective and bi-objective variants.

Suggested Citation

  • Lamiaa Dahite & Abdeslam Kadrani & Rachid Benmansour & Rym Nesrine Guibadj & Cyril Fonlupt, 2022. "Multi-Objective Model and Variable Neighborhood Search Algorithms for the Joint Maintenance Scheduling and Workforce Routing Problem," Mathematics, MDPI, vol. 10(11), pages 1-37, May.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1807-:d:823640
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/11/1807/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/11/1807/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abraham Duarte & Juan Pantrigo & Eduardo Pardo & Nenad Mladenovic, 2015. "Multi-objective variable neighborhood search: an application to combinatorial optimization problems," Journal of Global Optimization, Springer, vol. 63(3), pages 515-536, November.
    2. Dubois-Lacoste, Jérémie & López-Ibáñez, Manuel & Stützle, Thomas, 2015. "Anytime Pareto local search," European Journal of Operational Research, Elsevier, vol. 243(2), pages 369-385.
    3. López-Santana, Eduyn & Akhavan-Tabatabaei, Raha & Dieulle, Laurence & Labadie, Nacima & Medaglia, Andrés L., 2016. "On the combined maintenance and routing optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 199-214.
    4. Jbili, S. & Chelbi, A. & Radhoui, M. & Kessentini, M., 2018. "Integrated strategy of Vehicle Routing and Maintenance," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 202-214.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin, Boliang & Wu, Jianping & Lin, Ruixi & Wang, Jiaxi & Wang, Hui & Zhang, Xuhui, 2019. "Optimization of high-level preventive maintenance scheduling for high-speed trains," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 261-275.
    2. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    3. Nguyen, Ho Si Hung & Do, Phuc & Vu, Hai-Canh & Iung, Benoit, 2019. "Dynamic maintenance grouping and routing for geographically dispersed production systems," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 392-404.
    4. Albert H. Schrotenboer & Evrim Ursavas & Iris F. A. Vis, 2019. "A Branch-and-Price-and-Cut Algorithm for Resource-Constrained Pickup and Delivery Problems," Transportation Science, INFORMS, vol. 53(4), pages 1001-1022, July.
    5. John E. Fontecha & Oscar O. Guaje & Daniel Duque & Raha Akhavan-Tabatabaei & Juan P. Rodríguez & Andrés L. Medaglia, 2020. "Combined maintenance and routing optimization for large-scale sewage cleaning," Annals of Operations Research, Springer, vol. 286(1), pages 441-474, March.
    6. Havinga, Maik J.A. & de Jonge, Bram, 2020. "Condition-based maintenance in the cyclic patrolling repairman problem," International Journal of Production Economics, Elsevier, vol. 222(C).
    7. Dilaver, Halit Metehan & Akçay, Alp & van Houtum, Geert-Jan, 2023. "Integrated planning of asset-use and dry-docking for a fleet of maritime assets," International Journal of Production Economics, Elsevier, vol. 256(C).
    8. Alexandre D. Jesus & Luís Paquete & Arnaud Liefooghe, 2021. "A model of anytime algorithm performance for bi-objective optimization," Journal of Global Optimization, Springer, vol. 79(2), pages 329-350, February.
    9. Xiang Song & Dylan Jones & Nasrin Asgari & Tim Pigden, 2020. "Multi-objective vehicle routing and loading with time window constraints: a real-life application," Annals of Operations Research, Springer, vol. 291(1), pages 799-825, August.
    10. Eduardo G. Pardo & Antonio García-Sánchez & Marc Sevaux & Abraham Duarte, 2020. "Basic variable neighborhood search for the minimum sitting arrangement problem," Journal of Heuristics, Springer, vol. 26(2), pages 249-268, April.
    11. Abraham Duarte & Eduardo G. Pardo, 2020. "Special issue on recent innovations in variable neighborhood search," Journal of Heuristics, Springer, vol. 26(3), pages 335-338, June.
    12. Wu, Weitiao & Li, Yu, 2024. "Pareto truck fleet sizing for bike relocation with stochastic demand: Risk-averse multi-stage approximate stochastic programming," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    13. Pablo A. Miranda-Gonzalez & Javier Maturana-Ross & Carola A. Blazquez & Guillermo Cabrera-Guerrero, 2021. "Exact Formulation and Analysis for the Bi-Objective Insular Traveling Salesman Problem," Mathematics, MDPI, vol. 9(21), pages 1-33, October.
    14. Malek Ben Mechlia & Jérémie Schutz & Sofiene Dellagi & Anis Chelbi, 2021. "Quasi-Optimal Sizing of a Vehicle Fleet Considering Environmental Impact, Maintenance, and Eventual Containment Measures," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    15. Yıldız, Gazi Bilal & Soylu, Banu, 2019. "A multiobjective post-sales guarantee and repair services network design problem," International Journal of Production Economics, Elsevier, vol. 216(C), pages 305-320.
    16. Iliopoulou, Christina & Makridis, Michail A., 2023. "Critical multi-link disruption identification for public transport networks: A multi-objective optimization framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    17. Soylu, Banu & Katip, Hatice, 2019. "A multiobjective hub-airport location problem for an airline network design," European Journal of Operational Research, Elsevier, vol. 277(2), pages 412-425.
    18. Si, Guojin & Xia, Tangbin & Zhu, Ying & Du, Shichang & Xi, Lifeng, 2019. "Triple-level opportunistic maintenance policy for leasehold service network of multi-location production lines," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    19. Wu, Xueqi & Che, Ada, 2020. "Energy-efficient no-wait permutation flow shop scheduling by adaptive multi-objective variable neighborhood search," Omega, Elsevier, vol. 94(C).
    20. Mori, Masakatsu & Kobayashi, Ryoji & Samejima, Masaki & Komoda, Norihisa, 2017. "Risk-cost optimization for procurement planning in multi-tier supply chain by Pareto Local Search with relaxed acceptance criterion," European Journal of Operational Research, Elsevier, vol. 261(1), pages 88-96.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1807-:d:823640. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.