IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v5y2021i3p61-d629696.html
   My bibliography  Save this article

Sustainable Logistics Network Design for Delivery Operations with Time Horizons in B2B E-Commerce Platform

Author

Listed:
  • Dhirendra Prajapati

    (Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur 482005, India)

  • M. Manoj Kumar

    (Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur 482005, India)

  • Saurabh Pratap

    (Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India)

  • H. Chelladurai

    (Department of Mechanical Engineering, Indian Institute of Information Technology, Jabalpur 482005, India)

  • Mohd Zuhair

    (Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India)

Abstract

In the recent era, the rapidly increasing trend of e-commerce business creates opportunities for logistics service providers to grow globally. With this growth, the concern regarding the implementation of sustainability in logistic networks has received attention in recent years. Thus, in this work, we have focused on the vehicle routing problem (VRP) to deliver the products in a lesser time horizon with driver safety concern considerations in business (B2B) e-commerce platforms. We proposed a sustainable logistics network that captures the complexities of suppliers, retailers, and logistics service providers. A mixed-integer nonlinear programming (MINLP) approach is applied to formulate a model to minimize total time associated with order processing, handling, packaging, shipping, and vehicle maintenance. Branch-and-bound algorithms in the LINGO optimization tool and genetic algorithm (GA) are used to solve the formulated mathematical model. The computational experiments are performed in eight different case scenarios (small-sized problem to large-sized problem) to validate the model.

Suggested Citation

  • Dhirendra Prajapati & M. Manoj Kumar & Saurabh Pratap & H. Chelladurai & Mohd Zuhair, 2021. "Sustainable Logistics Network Design for Delivery Operations with Time Horizons in B2B E-Commerce Platform," Logistics, MDPI, vol. 5(3), pages 1-13, September.
  • Handle: RePEc:gam:jlogis:v:5:y:2021:i:3:p:61-:d:629696
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/5/3/61/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2305-6290/5/3/61/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huey-Kuo Chen & Huey-Wen Chou & Chia-Yuan Hsu, 2011. "The Linehaul-Feeder Vehicle Routing Problem with Virtual Depots and Time Windows," Mathematical Problems in Engineering, Hindawi, vol. 2011, pages 1-15, December.
    2. Subramanyam, Anirudh & Wang, Akang & Gounaris, Chrysanthos E., 2018. "A scenario decomposition algorithm for strategic time window assignment vehicle routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 296-317.
    3. Chen, Tzu-Li & Cheng, Chen-Yang & Chen, Yin-Yann & Chan, Li-Kai, 2015. "An efficient hybrid algorithm for integrated order batching, sequencing and routing problem," International Journal of Production Economics, Elsevier, vol. 159(C), pages 158-167.
    4. Mahdi Yousefi Nejad Attari & Ali Ebadi Torkayesh & Behnam Malmir & Ensiyeh Neyshabouri Jami, 2021. "Robust possibilistic programming for joint order batching and picker routing problem in warehouse management," International Journal of Production Research, Taylor & Francis Journals, vol. 59(14), pages 4434-4452, July.
    5. Rincon-Garcia, Nicolas & Waterson, Ben & Cherrett, Tom J. & Salazar-Arrieta, Fernando, 2020. "A metaheuristic for the time-dependent vehicle routing problem considering driving hours regulations – An application in city logistics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 429-446.
    6. Erfan Babaee Tirkolaee & Ali Asghar Rahmani Hosseinabadi & Mehdi Soltani & Arun Kumar Sangaiah & Jin Wang, 2018. "A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services," Sustainability, MDPI, vol. 10(5), pages 1-21, April.
    7. Neves-Moreira, Fábio & Amorim-Lopes, Mário & Amorim, Pedro, 2020. "The multi-period vehicle routing problem with refueling decisions: Traveling further to decrease fuel cost?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    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. Shengliang Zong & Chunyang Shen, 2023. "Decision-making and coordination in an e-commerce supply chain under channel selection," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 326-369, March.
    2. Rushikesh A. Patil & Abhishek D. Patange & Sujit S. Pardeshi, 2023. "International Transportation Mode Selection through Total Logistics Cost-Based Intelligent Approach," Logistics, MDPI, vol. 7(3), pages 1-26, September.
    3. Jose Alejandro Cano & Abraham Londoño-Pineda & Carolina Rodas, 2022. "Sustainable Logistics for E-Commerce: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    4. Prajapati, Dhirendra & Pratap, Saurabh & Zhang, Mengdi & Lakshay, & Huang, George Q., 2022. "Sustainable forward-reverse logistics for multi-product delivery and pickup in B2C E-commerce towards the circular economy," International Journal of Production Economics, Elsevier, vol. 253(C).

    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. Pardo, Eduardo G. & Gil-Borrás, Sergio & Alonso-Ayuso, Antonio & Duarte, Abraham, 2024. "Order batching problems: Taxonomy and literature review," European Journal of Operational Research, Elsevier, vol. 313(1), pages 1-24.
    2. van Gils, Teun & Ramaekers, Katrien & Braekers, Kris & Depaire, Benoît & Caris, An, 2018. "Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 243-261.
    3. Grzegorz Tarczyński, 2023. "Linear programming models for optimal workload and batching in pick-and-pass warehousing systems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(3), pages 141-158.
    4. Ping Liu & Jin Wang & Arun Kumar Sangaiah & Yang Xie & Xinchun Yin, 2019. "Analysis and Prediction of Water Quality Using LSTM Deep Neural Networks in IoT Environment," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
    5. Jin Wang & Yu Gao & Wei Liu & Arun Kumar Sangaiah & Hye-Jin Kim, 2019. "An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(3), pages 15501477198, March.
    6. Ahmad Ebrahimi & Hyun-woo Jeon & Sang-yeop Jung, 2023. "Improving Energy Consumption and Order Tardiness in Picker-to-Part Warehouses with Electric Forklifts: A Comparison of Four Evolutionary Algorithms," Sustainability, MDPI, vol. 15(13), pages 1-28, July.
    7. Xiaoqiu Shi & Wei Long & Yanyan Li & Dingshan Deng, 2020. "Multi-population genetic algorithm with ER network for solving flexible job shop scheduling problems," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-23, May.
    8. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    9. Fan, Tijun & Pan, Qianlan & Pan, Fei & Zhou, Wei & Chen, Jingyi, 2020. "Intelligent logistics integration of internal and external transportation with separation mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    10. Minfang Huang & Qiong Guo & Jing Liu & Xiaoxu Huang, 2018. "Mixed Model Assembly Line Scheduling Approach to Order Picking Problem in Online Supermarkets," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    11. Li Zhou & Huwei Liu & Junhui Zhao & Fan Wang & Jianglong Yang, 2022. "Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse," Mathematics, MDPI, vol. 10(17), pages 1-28, September.
    12. Žulj, Ivan & Salewski, Hagen & Goeke, Dominik & Schneider, Michael, 2022. "Order batching and batch sequencing in an AMR-assisted picker-to-parts system," European Journal of Operational Research, Elsevier, vol. 298(1), pages 182-201.
    13. Ardjmand, Ehsan & Shakeri, Heman & Singh, Manjeet & Sanei Bajgiran, Omid, 2018. "Minimizing order picking makespan with multiple pickers in a wave picking warehouse," International Journal of Production Economics, Elsevier, vol. 206(C), pages 169-183.
    14. Çağla Cergibozan & A. Serdar Tasan, 2022. "Genetic algorithm based approaches to solve the order batching problem and a case study in a distribution center," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 137-149, January.
    15. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    16. Falkenberg, Sven F. & Spinler, Stefan & Strauss, Arne K., 2024. "An algorithm for flexible transshipments with perfect synchronization," European Journal of Operational Research, Elsevier, vol. 315(3), pages 913-925.
    17. van Gils, Teun & Caris, An & Ramaekers, Katrien & Braekers, Kris, 2019. "Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse," European Journal of Operational Research, Elsevier, vol. 277(3), pages 814-830.
    18. Guo, Feng & Wei, Qu & Wang, Miao & Guo, Zhaoxia & Wallace, Stein W., 2023. "Deep attention models with dimension-reduction and gate mechanisms for solving practical time-dependent vehicle routing problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    19. Masae, Makusee & Glock, Christoph H. & Vichitkunakorn, Panupong, 2021. "A method for efficiently routing order pickers in the leaf warehouse," International Journal of Production Economics, Elsevier, vol. 234(C).
    20. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.

    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:jlogis:v:5:y:2021:i:3:p:61-:d:629696. 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.