IDEAS home Printed from https://ideas.repec.org/h/lum/prchap/01-44.html
   My bibliography  Save this book chapter

A New Approach Integrated for Optimizing the Materials Flow in Production

In: Rethinking Social Action. Core Values in Practice

Author

Listed:
  • Lucia-Violeta MELNIC

    (Associate Professor Ph.D, Ovidius University Constanta, Romania)

  • Gabriela IANCULESCU

    (Lecturer Ph.D, Ovidius University Constanta, Romania)

  • Andrei-Marian GURAU

    (Assistant Ph.D, Ovidius University Constanta, Romania)

Abstract

The production diversification and flexibility have complicated the activities in the field of production management. In these circumstances, researchers and operational managers feel, increasingly more, lack of an integrated model of synthetic industrial undertaking assigned to "black box" of it, namely the system of production. The mixt programming and allocation problem of production tasks can be dealt with in terms of optimizing the materials flow addressed as a whole in the production system. The present work presents a model for balancing the materials flow, which is based on the formal representation of the materials flow and which introduce elements of certain novelty, as well of matrix flow, the laws of evolution of the materials flow and others. The logic of materials flow formalization allows dynamic adaptive modelling and constitute the basic premise of the problem of programming and the allocation of production tasks. The emergent behavior of materials flow along with the structure of Production Planning System lead to a new logistics concept, that of Adaptive System of Production Planning and this through the development and analysis of material flow formalization elements. The main formalization elements are structured holistically and transdisciplinary as elements linking the operational management of production and operational management of the projects so that the elements of Operational Management of Production Projects.

Suggested Citation

  • Lucia-Violeta MELNIC & Gabriela IANCULESCU & Andrei-Marian GURAU, 2017. "A New Approach Integrated for Optimizing the Materials Flow in Production," Book chapters-LUMEN Proceedings, in: Camelia IGNATESCU & Antonio SANDU & Tomita CIULEI (ed.), Rethinking Social Action. Core Values in Practice, edition 1, volume 1, chapter 44, pages 483-495, Editura Lumen.
    • Handle: RePEc:lum:prchap:01-44
    DOI: https://doi.org/10.18662/lumproc.rsacvp2017.44
    as

    Download full text from publisher

    File URL: https://proceedings.lumenpublishing.com/ojs/index.php/lumenproceedings/article/view/449/453
    Download Restriction: no
    File URL: https://proceedings.lumenpublishing.com/ojs/index.php/lumenproceedings/article/view/449
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.18662/lumproc.rsacvp2017.44?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. Blazewicz, Jacek & Domschke, Wolfgang & Pesch, Erwin, 1996. "The job shop scheduling problem: Conventional and new solution techniques," European Journal of Operational Research, Elsevier, vol. 93(1), pages 1-33, August.
    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. Rossi, Andrea, 2014. "Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships," International Journal of Production Economics, Elsevier, vol. 153(C), pages 253-267.
    2. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    3. Jacomine Grobler & Andries Engelbrecht & Schalk Kok & Sarma Yadavalli, 2010. "Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time," Annals of Operations Research, Springer, vol. 180(1), pages 165-196, November.
    4. Pempera, Jaroslaw & Smutnicki, Czeslaw, 2018. "Open shop cyclic scheduling," European Journal of Operational Research, Elsevier, vol. 269(2), pages 773-781.
    5. Drexl, A. & Kimms, A., 1997. "Lot sizing and scheduling -- Survey and extensions," European Journal of Operational Research, Elsevier, vol. 99(2), pages 221-235, June.
    6. Honorine Harlé & Sophie Hooge & Pascal Le Masson & Kevin Levillain & Benoit Weil & Guillaume Bulin & Thierry Menard, 2019. "Innovative design in factory: new methods to go from closed to expandable prescriptions at the shop floor," Post-Print hal-02094246, HAL.
    7. Honorine Harlé & Sophie Hooge & Pascal Le Masson & Kevin Levillain & Benoit Weil & Guillaume Bulin & Thierry Menard, 2019. "Innovative design in factory: new methods to go from closed to expandable prescriptions at the shop floor," Working Papers hal-02094246, HAL.
    8. 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.
    9. Roland Braune, 2022. "Packing-based branch-and-bound for discrete malleable task scheduling," Journal of Scheduling, Springer, vol. 25(6), pages 675-704, December.
    10. A. R. Rahimi-Vahed & S. M. Mirghorbani, 2007. "A multi-objective particle swarm for a flow shop scheduling problem," Journal of Combinatorial Optimization, Springer, vol. 13(1), pages 79-102, January.
    11. 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.
    12. Monaci, Marta & Agasucci, Valerio & Grani, Giorgio, 2024. "An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents," European Journal of Operational Research, Elsevier, vol. 312(3), pages 910-926.
    13. Anna Ławrynowicz, 2006. "Hybrid approach with an expert system and a genetic algorithm to production management in the supply net," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 14(1‐2), pages 59-76, January.
    14. Giuseppe Lancia & Franca Rinaldi & Paolo Serafini, 2011. "A time-indexed LP-based approach for min-sum job-shop problems," Annals of Operations Research, Springer, vol. 186(1), pages 175-198, June.
    15. Christoph Schuster, 2006. "No-wait Job Shop Scheduling: Tabu Search and Complexity of Subproblems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 63(3), pages 473-491, July.
    16. J. Christopher Beck & T. K. Feng & Jean-Paul Watson, 2011. "Combining Constraint Programming and Local Search for Job-Shop Scheduling," INFORMS Journal on Computing, INFORMS, vol. 23(1), pages 1-14, February.
    17. Raaymakers, W. H. M. & Hoogeveen, J. A., 2000. "Scheduling multipurpose batch process industries with no-wait restrictions by simulated annealing," European Journal of Operational Research, Elsevier, vol. 126(1), pages 131-151, October.
    18. Kurowski, Krzysztof & Pecyna, Tomasz & Slysz, Mateusz & Różycki, Rafał & Waligóra, Grzegorz & Wȩglarz, Jan, 2023. "Application of quantum approximate optimization algorithm to job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 310(2), pages 518-528.
    19. Thi-Kien Dao & Tien-Szu Pan & Trong-The Nguyen & Jeng-Shyang Pan, 2018. "Parallel bat algorithm for optimizing makespan in job shop scheduling problems," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 451-462, February.
    20. A Ławrynowicz, 2008. "Integration of production planning and scheduling using an expert system and a genetic algorithm," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 455-463, April.

    More about this item

    Keywords

    transdisciplinary; knowledge; production; material flow;
    All these keywords.

    JEL classification:

    • A3 - General Economics and Teaching - - Multisubject Collective Works
    • I2 - Health, Education, and Welfare - - Education
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General

    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:lum:prchap:01-44. 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: Antonio Sandu (email available below). General contact details of provider: https://proceedings.lumenpublishing.com/ojs/index.php/lumenproceedings .

    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.