IDEAS home Printed from https://ideas.repec.org/a/hin/complx/5180156.html
   My bibliography  Save this article

Smart Scheduling: An Integrated First Mile and Last Mile Supply Approach

Author

Listed:
  • Tamás Bányai
  • Béla Illés
  • Ágota Bányai

Abstract

Supply chain management applies more and more Industry 4.0 innovations to increase their availability, elasticity, sustainability, and efficiency. In interconnected logistics networks, operations are integrated from suppliers through 3rd party logistics providers to customers. There are different delivery models depending on the time and cost. In the last few years, a wide range of customers is willing to pay an extra fee for the same delivery or instant delivery. This fact led to the increased importance of the optimized design and control of first mile/last mile (FMLM) delivery solutions. Cyberphysical system-based service innovations make it possible to enhance the productivity of FMLM delivery in the big data environment. The design and operation problems can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on heuristic and metaheuristic algorithms. This research proposes an integrated supply model of FMLM delivery. After a careful literature review, this paper introduces a mathematical model to formulate the problem of real-time smart scheduling of FMLM delivery. The integrated model includes the assignment of first mile and last mile delivery tasks to the available resources and the optimization of operations costs, while constraints like capacity, time window, and availability are taken into consideration. Next, a black hole optimization- (BHO-) based algorithm dealing with a multiobjective supply chain model is presented. The sensitivity of the enhanced algorithm is tested with benchmark functions. Numerical results with different datasets demonstrate the efficiency of the proposed model and validate the usage of Industry 4.0 inventions in FMLM delivery.

Suggested Citation

  • Tamás Bányai & Béla Illés & Ágota Bányai, 2018. "Smart Scheduling: An Integrated First Mile and Last Mile Supply Approach," Complexity, Hindawi, vol. 2018, pages 1-15, July.
  • Handle: RePEc:hin:complx:5180156
    DOI: 10.1155/2018/5180156
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/5180156.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2018/5180156.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2018/5180156?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Chunlei Tang, 2021. "Introduction," Springer Books, in: Data Capital, chapter 0, pages 1-32, Springer.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Techane Bosona, 2020. "Urban Freight Last Mile Logistics—Challenges and Opportunities to Improve Sustainability: A Literature Review," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    2. Elifcan Göçmen & Rızvan Erol, 2018. "The Problem of Sustainable Intermodal Transportation: A Case Study of an International Logistics Company, Turkey," Sustainability, MDPI, vol. 10(11), pages 1-16, November.

    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. Shaoxuan Liu & Kut C. So & Fuqiang Zhang, 2010. "Effect of Supply Reliability in a Retail Setting with Joint Marketing and Inventory Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 19-32, March.
    2. Sirong Chen & Rob Law & Shaogui Xu & Mu Zhang, 2020. "Bibliometric and Visualized Analysis of Mobile Technology in Tourism," Sustainability, MDPI, vol. 12(19), pages 1-16, September.
    3. Sahar Afshan & Arshian Sharif & Abdelmohsen A. Nassani & Muhammad M. Q. Abro & Rubeena Batool & Khalid Zaman, 2021. "The role of information and communication technology (internet penetration) on Asian stock market efficiency: Evidence from quantile‐on‐quantile cointegration and causality approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2307-2324, April.
    4. Sundar Bharadwaj & Anandhi Bharadwaj & Elliot Bendoly, 2007. "The Performance Effects of Complementarities Between Information Systems, Marketing, Manufacturing, and Supply Chain Processes," Information Systems Research, INFORMS, vol. 18(4), pages 437-453, December.
    5. Amar Sapra & Van-Anh Truong & Rachel Q. Zhang, 2010. "How Much Demand Should Be Fulfilled?," Operations Research, INFORMS, vol. 58(3), pages 719-733, June.
    6. Jianyu Li & Hong Li & Zheming Zhu & Ye Tao & Chun’an Tang, 2021. "Numerical Study on Damage Zones Induced by Excavation and Ventilation in a High-Temperature Tunnel at Depth," Energies, MDPI, vol. 14(16), pages 1-20, August.
    7. So Yeon Chun & Dan A. Iancu & Nikolaos Trichakis, 2020. "Loyalty Program Liabilities and Point Values," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 257-272, March.
    8. Gregory J. King & Xiuli Chao & Izak Duenyas, 2019. "Who Benefits When Prescription Drug Manufacturers Offer Copay Coupons?," Management Science, INFORMS, vol. 65(8), pages 3758-3775, August.
    9. Assumpció Huertas & Antonio Moreno & Jordi Pascual, 2021. "Place Branding for Smart Cities and Smart Tourism Destinations: Do They Communicate Their Smartness?," Sustainability, MDPI, vol. 13(19), pages 1-18, October.
    10. Eric T. Anderson & Karsten Hansen & Duncan Simester, 2009. "The Option Value of Returns: Theory and Empirical Evidence," Marketing Science, INFORMS, vol. 28(3), pages 405-423, 05-06.
    11. Jesus Felix Bayta Valenzuela & Xiuju Fu & Gaoxi Xiao & Rick Siow Mong Goh, 2018. "A Network-Based Impact Measure for Propagated Losses in a Supply Chain Network Consisting of Resilient Components," Complexity, Hindawi, vol. 2018, pages 1-13, February.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:5180156. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.