IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i18p3983-d1243334.html
   My bibliography  Save this article

Delivery Times Scheduling with Deterioration Effects in Due Window Assignment Environments

Author

Listed:
  • Rong-Rong Mao

    (School of Economics and Management, Shenyang Aerospace University, Shenyang 110136, China)

  • Yi-Chun Wang

    (School of Economics and Management, Shenyang Aerospace University, Shenyang 110136, China)

  • Dan-Yang Lv

    (School of Economics and Management, Shenyang Aerospace University, Shenyang 110136, China)

  • Ji-Bo Wang

    (School of Economics and Management, Shenyang Aerospace University, Shenyang 110136, China)

  • Yuan-Yuan Lu

    (College of Mathematics and Computer, Jilin Normal University, Siping 136000, China)

Abstract

In practical problems, in addition to the processing time of the job, the impact of the time required for delivering the service to customers on the cost is also considered, i.e., delivery time, where the job processing time is a simple linear function of its starting time. This paper considers the impact of past-sequence-dependent delivery times (which can be referred to as p s d d t ) on the studied objectives in three types of due windows (common, slack and different due windows). This serves to minimize the weighted sum of earliness, tardiness, starting time and size of due window, where the weights (coefficients) are related to the location. Through the theoretical analysis of the optimal solution, it is found that these three problems can be solved in time O ( N log N ) , respectively, where N is the number of jobs.

Suggested Citation

  • Rong-Rong Mao & Yi-Chun Wang & Dan-Yang Lv & Ji-Bo Wang & Yuan-Yuan Lu, 2023. "Delivery Times Scheduling with Deterioration Effects in Due Window Assignment Environments," Mathematics, MDPI, vol. 11(18), pages 1-18, September.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3983-:d:1243334
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/18/3983/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/18/3983/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wenhua Li & Libo Wang & Xing Chai & Hang Yuan, 2020. "Online Batch Scheduling of Simple Linear Deteriorating Jobs with Incompatible Families," Mathematics, MDPI, vol. 8(2), pages 1-12, February.
    2. Koulamas, Christos & Kyparisis, George J., 2010. "Single-machine scheduling problems with past-sequence-dependent delivery times," International Journal of Production Economics, Elsevier, vol. 126(2), pages 264-266, August.
    3. Lei Pan & Xinyu Sun & Ji-Bo Wang & Li-Han Zhang & Dan-Yang Lv, 2023. "Due date assignment single-machine scheduling with delivery times, position-dependent weights and deteriorating jobs," Journal of Combinatorial Optimization, Springer, vol. 45(4), pages 1-16, May.
    4. Cuixia Miao & Jiaxin Song & Yuzhong Zhang, 2023. "Single-Machine Time-Dependent Scheduling with Proportional and Delivery Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 40(04), pages 1-12, August.
    5. Jin Qian & Yu Zhan, 2022. "The Due Window Assignment Problems with Deteriorating Job and Delivery Time," Mathematics, MDPI, vol. 10(10), pages 1-16, May.
    6. Janiak, Adam & Janiak, Władysław A. & Krysiak, Tomasz & Kwiatkowski, Tomasz, 2015. "A survey on scheduling problems with due windows," European Journal of Operational Research, Elsevier, vol. 242(2), pages 347-357.
    7. Xinyu Sun & Xin-Na Geng, 2019. "Single-machine scheduling with deteriorating effects and machine maintenance," International Journal of Production Research, Taylor & Francis Journals, vol. 57(10), pages 3186-3199, May.
    8. Jun Pei & Ya Zhou & Ping Yan & Panos M. Pardalos, 2023. "A concise guide to scheduling with learning and deteriorating effects," International Journal of Production Research, Taylor & Francis Journals, vol. 61(6), pages 2010-2031, March.
    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. Hongyu He & Yanzhi Zhao & Xiaojun Ma & Yuan-Yuan Lu & Na Ren & Ji-Bo Wang, 2023. "Study on Scheduling Problems with Learning Effects and Past Sequence Delivery Times," Mathematics, MDPI, vol. 11(19), pages 1-19, September.
    2. Zheng-Guo Lv & Li-Han Zhang & Xiao-Yuan Wang & Ji-Bo Wang, 2024. "Single Machine Scheduling Proportionally Deteriorating Jobs with Ready Times Subject to the Total Weighted Completion Time Minimization," Mathematics, MDPI, vol. 12(4), pages 1-15, February.
    3. Xinyu Sun & Xin-Na Geng & Tao Liu, 2020. "Due-window assignment scheduling in the proportionate flow shop setting," Annals of Operations Research, Springer, vol. 292(1), pages 113-131, September.
    4. Javad Rezaeian & Reza Alizadeh Foroutan & Toraj Mojibi & Yacob Khojasteh, 2023. "Sensitivity Analysis of the Unrelated Parallel Machine Scheduling Problem with Rework Processes and Machine Eligibility Restrictions," SN Operations Research Forum, Springer, vol. 4(3), pages 1-24, September.
    5. Lei Pan & Xinyu Sun & Ji-Bo Wang & Li-Han Zhang & Dan-Yang Lv, 2023. "Due date assignment single-machine scheduling with delivery times, position-dependent weights and deteriorating jobs," Journal of Combinatorial Optimization, Springer, vol. 45(4), pages 1-16, May.
    6. Li-Han Zhang & Dan-Yang Lv & Ji-Bo Wang, 2023. "Two-Agent Slack Due-Date Assignment Scheduling with Resource Allocations and Deteriorating Jobs," Mathematics, MDPI, vol. 11(12), pages 1-12, June.
    7. Dujuan Wang & Yunqiang Yin & T.C.E. Cheng, 2017. "A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(1), pages 41-63, February.
    8. Xinyu Sun & Tao Liu & Xin-Na Geng & Yang Hu & Jing-Xiao Xu, 2023. "Optimization of scheduling problems with deterioration effects and an optional maintenance activity," Journal of Scheduling, Springer, vol. 26(3), pages 251-266, June.
    9. Feng Li & Zhi-Long Chen & Zhi-Long Chen, 2017. "Integrated Production, Inventory and Delivery Problems: Complexity and Algorithms," INFORMS Journal on Computing, INFORMS, vol. 29(2), pages 232-250, May.
    10. Yunqiang Yin & Du-Juan Wang & T C E Cheng & Chin-Chia Wu, 2016. "Bi-criterion single-machine scheduling and due-window assignment with common flow allowances and resource-dependent processing times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(9), pages 1169-1183, September.
    11. Yi-Chun Wang & Si-Han Wang & Ji-Bo Wang, 2023. "Resource Allocation Scheduling with Position-Dependent Weights and Generalized Earliness–Tardiness Cost," Mathematics, MDPI, vol. 11(1), pages 1-11, January.
    12. Söhnke Maecker & Liji Shen, 2020. "Solving parallel machine problems with delivery times and tardiness objectives," Annals of Operations Research, Springer, vol. 285(1), pages 315-334, February.
    13. Jin Qian & Yu Zhan, 2022. "The Due Window Assignment Problems with Deteriorating Job and Delivery Time," Mathematics, MDPI, vol. 10(10), pages 1-16, May.
    14. Zhongyi Jiang & Fangfang Chen & Xiandong Zhang, 2017. "Single-machine scheduling with times-based and job-dependent learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 809-815, July.
    15. Baruch Mor, 2019. "Minmax scheduling problems with common due-date and completion time penalty," Journal of Combinatorial Optimization, Springer, vol. 38(1), pages 50-71, July.
    16. Shabtay, Dvir & Mosheiov, Gur & Oron, Daniel, 2022. "Single machine scheduling with common assignable due date/due window to minimize total weighted early and late work," European Journal of Operational Research, Elsevier, vol. 303(1), pages 66-77.
    17. Mor, Baruch & Mosheiov, Gur, 2016. "Minsum and minmax scheduling on a proportionate flowshop with common flow-allowance," European Journal of Operational Research, Elsevier, vol. 254(2), pages 360-370.
    18. Nils Boysen & Stefan Fedtke & Felix Weidinger, 2017. "Truck Scheduling in the Postal Service Industry," Transportation Science, INFORMS, vol. 51(2), pages 723-736, May.
    19. Xu, Shuling & Hall, Nicholas G., 2021. "Fatigue, personnel scheduling and operations: Review and research opportunities," European Journal of Operational Research, Elsevier, vol. 295(3), pages 807-822.
    20. Ji-Bo Wang & Bo Cui & Ping Ji & Wei-Wei Liu, 2021. "Research on single-machine scheduling with position-dependent weights and past-sequence-dependent delivery times," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 290-303, February.

    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:11:y:2023:i:18:p:3983-:d:1243334. 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.