IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i23p3030-d688474.html
   My bibliography  Save this article

One-Machine Scheduling with Time-Dependent Capacity via Efficient Memetic Algorithms

Author

Listed:
  • Raúl Mencía

    (Department of Computer Science, University of Oviedo, 33204 Gijón, Spain)

  • Carlos Mencía

    (Department of Computer Science, University of Oviedo, 33204 Gijón, Spain)

Abstract

This paper addresses the problem of scheduling a set of jobs on a machine with time-varying capacity, with the goal of minimizing the total tardiness objective function. This problem arose in the context scheduling the charging times of a fleet of electric vehicles and it is NP-hard. Recent work proposed an efficient memetic algorithm for solving the problem, combining a genetic algorithm and a local search method. The local search procedure is based on swapping consecutive jobs on a C-path, defined as a sequence of consecutive jobs in a schedule. Building on it, this paper develops new memetic algorithms that stem from new local search procedures also proposed in this paper. The local search methods integrate several mechanisms to make them more effective, including a new condition for swapping pairs of jobs, a hill climbing approach, a procedure that operates on several C-paths and a method that interchanges jobs between different C-paths. As a result, the new local search methods enable the memetic algorithms to reach higher-quality solutions. Experimental results show significant improvements over existing approaches.

Suggested Citation

  • Raúl Mencía & Carlos Mencía, 2021. "One-Machine Scheduling with Time-Dependent Capacity via Efficient Memetic Algorithms," Mathematics, MDPI, vol. 9(23), pages 1-24, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3030-:d:688474
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/23/3030/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/23/3030/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ari P. J. Vepsalainen & Thomas E. Morton, 1987. "Priority Rules for Job Shops with Weighted Tardiness Costs," Management Science, INFORMS, vol. 33(8), pages 1035-1047, August.
    2. Jianzhong Du & Joseph Y.-T. Leung, 1990. "Minimizing Total Tardiness on One Machine is NP-Hard," Mathematics of Operations Research, INFORMS, vol. 15(3), pages 483-495, August.
    3. Gonçalves, J.F. & Mendes, J.J.M. & Resende, M.G.C., 2008. "A genetic algorithm for the resource constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1171-1190, September.
    4. Carlier, Jacques, 1982. "The one-machine sequencing problem," European Journal of Operational Research, Elsevier, vol. 11(1), pages 42-47, September.
    5. Luis F. Machado-Domínguez & Carlos D. Paternina-Arboleda & Jorge I. Vélez & Agustin Barrios-Sarmiento, 2021. "A memetic algorithm to address the multi-node resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 24(4), pages 413-429, August.
    6. Franca, Paulo M. & Mendes, Alexandre & Moscato, Pablo, 2001. "A memetic algorithm for the total tardiness single machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 132(1), pages 224-242, July.
    7. Sprecher, Arno & Kolisch, Rainer & Drexl, Andreas, 1995. "Semi-active, active, and non-delay schedules for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 80(1), pages 94-102, January.
    8. Nicholas G. Hall & Chris N. Potts, 2003. "Supply chain scheduling: Batching and delivery," Operations Research, INFORMS, vol. 51(4), pages 566-584, August.
    9. Christos Koulamas, 1994. "The Total Tardiness Problem: Review and Extensions," Operations Research, INFORMS, vol. 42(6), pages 1025-1041, December.
    10. Onwubolu, Godfrey & Davendra, Donald, 2006. "Scheduling flow shops using differential evolution algorithm," European Journal of Operational Research, Elsevier, vol. 171(2), pages 674-692, June.
    11. Kolisch, Rainer, 1996. "Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation," European Journal of Operational Research, Elsevier, vol. 90(2), pages 320-333, April.
    12. Joseph Adams & Egon Balas & Daniel Zawack, 1988. "The Shifting Bottleneck Procedure for Job Shop Scheduling," Management Science, INFORMS, vol. 34(3), pages 391-401, March.
    13. Christian Artigues & Pierre Lopez & Pierre-Dimitri Ayache, 2005. "Schedule Generation Schemes for the Job-Shop Problem with Sequence-Dependent Setup Times: Dominance Properties and Computational Analysis," Annals of Operations Research, Springer, vol. 138(1), pages 21-52, September.
    14. Eduardo Queiroga & Rian G. S. Pinheiro & Quentin Christ & Anand Subramanian & Artur A. Pessoa, 2021. "Iterated local search for single machine total weighted tardiness batch scheduling," Journal of Heuristics, Springer, vol. 27(3), pages 353-438, June.
    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. Christian Artigues & Dominique Feillet, 2008. "A branch and bound method for the job-shop problem with sequence-dependent setup times," Annals of Operations Research, Springer, vol. 159(1), pages 135-159, March.
    2. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    3. C N Potts & V A Strusevich, 2009. "Fifty years of scheduling: a survey of milestones," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 41-68, May.
    4. Wenda Zhang & Jason J. Sauppe & Sheldon H. Jacobson, 2021. "An Improved Branch-and-Bound Algorithm for the One-Machine Scheduling Problem with Delayed Precedence Constraints," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1091-1102, July.
    5. Alidaee, Bahram & Kochenberger, Gary A. & Amini, Mohammad M., 2001. "Greedy solutions of selection and ordering problems," European Journal of Operational Research, Elsevier, vol. 134(1), pages 203-215, October.
    6. S. David Wu & Eui-Seok Byeon & Robert H. Storer, 1999. "A Graph-Theoretic Decomposition of the Job Shop Scheduling Problem to Achieve Scheduling Robustness," Operations Research, INFORMS, vol. 47(1), pages 113-124, February.
    7. Ullrich, Christian A., 2013. "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, Elsevier, vol. 227(1), pages 152-165.
    8. Schirmer, Andreas & Riesenberg, Sven, 1997. "Parameterized heuristics for project scheduling: Biased random sampling methods," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 456, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    9. Bierwirth, C. & Kuhpfahl, J., 2017. "Extended GRASP for the job shop scheduling problem with total weighted tardiness objective," European Journal of Operational Research, Elsevier, vol. 261(3), pages 835-848.
    10. Ansis Ozolins, 2020. "Bounded dynamic programming algorithm for the job shop problem with sequence dependent setup times," Operational Research, Springer, vol. 20(3), pages 1701-1728, September.
    11. S-W Lin & K-C Ying, 2008. "A hybrid approach for single-machine tardiness problems with sequence-dependent setup times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1109-1119, August.
    12. Goel, Asvin & Meisel, Frank, 2013. "Workforce routing and scheduling for electricity network maintenance with downtime minimization," European Journal of Operational Research, Elsevier, vol. 231(1), pages 210-228.
    13. Bouleimen, K. & Lecocq, H., 2003. "A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version," European Journal of Operational Research, Elsevier, vol. 149(2), pages 268-281, September.
    14. Sprecher, Arno, 1999. "Network decomposition techniques for resource-constrained project scheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 505, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    15. Egon Balas & Giuseppe Lancia & Paolo Serafini & Alkiviadis Vazacopoulos, 1998. "Job Shop Scheduling With Deadlines," Journal of Combinatorial Optimization, Springer, vol. 1(4), pages 329-353, December.
    16. Mattfeld, Dirk C. & Bierwirth, Christian, 2004. "An efficient genetic algorithm for job shop scheduling with tardiness objectives," European Journal of Operational Research, Elsevier, vol. 155(3), pages 616-630, June.
    17. Christos Koulamas, 1997. "Decomposition and hybrid simulated annealing heuristics for the parallel‐machine total tardiness problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(1), pages 109-125, February.
    18. Mukherjee, Saral & Chatterjee Ashis K, 2002. "Applying Machine Based Decomposition in 2-Machine Flow Shops," IIMA Working Papers WP2002-08-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    19. Jain, A. S. & Meeran, S., 1999. "Deterministic job-shop scheduling: Past, present and future," European Journal of Operational Research, Elsevier, vol. 113(2), pages 390-434, March.
    20. Sprecher, Arno, 1996. "Solving the RCPSP efficiently at modest memory requirements," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 425, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.

    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:9:y:2021:i:23:p:3030-:d:688474. 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.