IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v170y2021ics0040162521003218.html
   My bibliography  Save this article

Multi-layered coding-based study on optimization algorithms for automobile production logistics scheduling

Author

Listed:
  • Yue, Guo
  • Tailai, Guo
  • Dan, Wei

Abstract

With the acceleration of economic globalization, competition among manufacturing industries has become increasingly fierce. Automobile manufacturing has always been a critical investment and development industry in different countries. For the automobile manufacturing industry, the logistics scheduling problem of automobile production is affects automobile manufacturing enterprises’ ability to compete. This paper discusses disruptive technologies, such as AI, IoT, Big data, etc., to solve production problems. Therefore, production logistics systems research is essential to automobile manufacturing enterprises, to improve production efficiency, reduce production costs, and increase enterprises’ economic benefits. We present three kinds of mathematical models designed and calculated by a genetic algorithm, aimed at the Pareto solution set to solve multi-objective optimization, as well as designs for a new contrast flow, which can quickly find the optimal solution and simulate the algorithm.

Suggested Citation

  • Yue, Guo & Tailai, Guo & Dan, Wei, 2021. "Multi-layered coding-based study on optimization algorithms for automobile production logistics scheduling," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    • Handle: RePEc:eee:tefoso:v:170:y:2021:i:c:s0040162521003218
    DOI: 10.1016/j.techfore.2021.120889
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521003218
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2021.120889?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Victor Chang, 2020. "Presenting Cloud Business Performance for Manufacturing Organizations," Information Systems Frontiers, Springer, vol. 22(1), pages 59-75, February.
    2. Gabriela Slusariuc, 2003. "Consideration about the market of the motor industry," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 3, pages 209-212.
    3. Dario Dunkovic & Goran Jukic, 2010. "Quick Response Manufacturing(QRM) as a Reaction of Production Logistics on Cooperation with Retailers," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 10, pages 185-197.
    4. Rahman, Md Samsur & Khan, Faisal & Shaikh, Arifusalam & Ahmed, Salim & Imtiaz, Syed, 2020. "A conditional dependence-based marine logistics support risk model," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Feijóo, Claudio & Kwon, Youngsun & Bauer, Johannes M. & Bohlin, Erik & Howell, Bronwyn & Jain, Rekha & Potgieter, Petrus & Vu, Khuong & Whalley, Jason & Xia, Jun, 2020. "Harnessing artificial intelligence (AI) to increase wellbeing for all: The case for a new technology diplomacy," Telecommunications Policy, Elsevier, vol. 44(6).
    6. Sakawa, Masatoshi & Kubota, Ryo, 2000. "Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms," European Journal of Operational Research, Elsevier, vol. 120(2), pages 393-407, January.
    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. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    2. Zhou, Shengjia & Wang, Junhao & Xu, Bing, 2022. "Innovative coupling and coordination: Automobile and digital industries," Technological Forecasting and Social Change, Elsevier, vol. 176(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. Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan, 2022. "An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    2. Anurag Agarwal & Varghese S. Jacob & Hasan Pirkul, 2006. "An Improved Augmented Neural-Network Approach for Scheduling Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 119-128, February.
    3. Saima Javed & Yu Rong & Babar Nawaz Abbasi, 2024. "Convergence analysis of artificial intelligence research capacity: Are the less developed catching up with the developed ones?," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(4), pages 2172-2192, May.
    4. Ji, Chenyi & Su, Xing & Qin, Zhongfu & Nawaz, Ahsan, 2022. "Probability Analysis of Construction Risk based on Noisy-or Gate Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. John Oredo & Denis Dennehy, 2023. "Exploring the Role of Organizational Mindfulness on Cloud Computing and Firm Performance: The Case of Kenyan Organizations," Information Systems Frontiers, Springer, vol. 25(5), pages 2029-2050, October.
    6. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. D Petrovic & O Aköz, 2008. "A fuzzy goal programming approach to integrated loading and scheduling of a batch processing machine," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1211-1219, September.
    8. Levinson, Nanette S., 2021. "Idea entrepreneurs: The United Nations Open-Ended Working Group & cybersecurity," Telecommunications Policy, Elsevier, vol. 45(6).
    9. Adland, Roar & Jia, Haiying & Lode, Tønnes & Skontorp, Jørgen, 2021. "The value of meteorological data in marine risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    10. Radu, Roxana & Kettemann, Matthias C. & Meyer, Trisha & Shahin, Jamal, 2021. "Normfare: Norm entrepreneurship in internet governance," Telecommunications Policy, Elsevier, vol. 45(6).
    11. Ma, Chao-Qun & Lei, Yu-Tian & Ren, Yi-Shuai & Chen, Xun-Qi & Wang, Yi-Ran & Narayan, Seema, 2024. "Systematic analysis of the blockchain in the energy sector: Trends, issues, and future directions," Telecommunications Policy, Elsevier, vol. 48(2).
    12. Sanja Petrovic & Carole Fayad & Dobrila Petrovic & Edmund Burke & Graham Kendall, 2008. "Fuzzy job shop scheduling with lot-sizing," Annals of Operations Research, Springer, vol. 159(1), pages 275-292, March.
    13. Nayef Shaie Alotaibi & Awad Hajran Alshehri, 2023. "Prospers and Obstacles in Using Artificial Intelligence in Saudi Arabia Higher Education Institutions—The Potential of AI-Based Learning Outcomes," Sustainability, MDPI, vol. 15(13), pages 1-18, July.
    14. K A H Kobbacy & S Vadera & M H Rasmy, 2007. "AI and OR in management of operations: history and trends," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 10-28, January.
    15. Figueroa–García, Juan Carlos & Hernández, Germán & Franco, Carlos, 2022. "A review on history, trends and perspectives of fuzzy linear programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    16. Lei Wang & Provash Sarker & Kausar Alam & Shahneoaj Sumon, 2021. "Artificial Intelligence and Economic Growth: A Theoretical Framework," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 68(4), pages 421-443, November.
    17. Luda Zhao & Bin Wang & Congyong Shen, 2021. "A multi-objective scheduling method for operational coordination time using improved triangular fuzzy number representation," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-31, June.
    18. Paiola, Marco & Schiavone, Francesco & Khvatova, Tatiana & Grandinetti, Roberto, 2021. "Prior knowledge, industry 4.0 and digital servitization. An inductive framework," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    19. Gokhan Ozkaya & Ayse Demirhan, 2023. "Analysis of Countries in Terms of Artificial Intelligence Technologies: PROMETHEE and GAIA Method Approach," Sustainability, MDPI, vol. 15(5), pages 1-27, March.
    20. Ruipu Dong & Jinghua Li & Dening Song & Boxin Yang & Lei Zhou, 2024. "A Multi-Objective Non-Dominated Sorting Gravitational Search Algorithm for Assembly Flow-Shop Scheduling of Marine Prefabricated Cabins," Mathematics, MDPI, vol. 12(14), pages 1-32, July.

    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:eee:tefoso:v:170:y:2021:i:c:s0040162521003218. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.