- -

Enfoque híbrido metaheurístico AG-RS para el problema de asignación del buffer que minimiza el inventario en proceso en líneas de producción abiertas en serie

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Enfoque híbrido metaheurístico AG-RS para el problema de asignación del buffer que minimiza el inventario en proceso en líneas de producción abiertas en serie

Show full item record

Hernández-Vázquez, JO.; Hernández-González, S.; Jiménez-García, JA.; Hernández-Ripalda, MD.; Hernández-Vázquez, JI. (2019). Enfoque híbrido metaheurístico AG-RS para el problema de asignación del buffer que minimiza el inventario en proceso en líneas de producción abiertas en serie. Revista Iberoamericana de Automática e Informática. 16(4):447-458. https://doi.org/10.4995/riai.2019.10883

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/126290

Files in this item

Item Metadata

Title: Enfoque híbrido metaheurístico AG-RS para el problema de asignación del buffer que minimiza el inventario en proceso en líneas de producción abiertas en serie
Secondary Title: Hybrid metaheuristic approach GA-SA for the buffer allocation problem that minimizes the work in process in open serial production lines
Author:
Issued date:
Abstract:
[EN] The Buffer Allocation Problem (BAP) is a problem of combinatorial NP-Hard optimization in the design of production lines. This consists of defining the allocation of storage places (buffers) within a production line, ...[+]


[ES] El problema de asignación del buffer (BAP, por sus siglas en inglés) es clasificado como un problema de optimización combinatorio NP-Duro en el diseño de las líneas de producción. Éste consiste en definir la asignación ...[+]
Subjects: Control de inventario , Optimización y métodos computacionales , BAP , Metaheurísticas híbridas , Líneas de producción , Inventory control , Optimization and computational methods , Hybrid metaheuristics , Production lines
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Revista Iberoamericana de Automática e Informática.. (issn: 1697-7912 ) (eissn: 1697-7920 )
DOI: 10.4995/riai.2019.10883
Publisher:
1697-7912
Publisher version: https://doi.org/10.4995/riai.2019.10883
Thanks:
Se agradece al Consejo Nacional de Ciencia y Tecnología (CONACYT) por el financiamiento de esta investigación con número de registro CVU: 375571. Un reconocimiento a Juana Cinthia Lizbeth Nava Torres, Rafael Paniagua ...[+]
Type: Artículo

References

Amiri, M., & Mohtashami, A. (2011). Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm. International Journal of Advanced Manufacturing Technology, 62, 371-383. https://doi.org/10.1007/s00170-011-3802-8

Ariyani, A. K., Mahmudy, W. F., & Anggodo, Y. P. (2018). Hybrid genetic algorithms and simulated annealing for multi-trip vehicle routing problem with time windows. International Journal of Electrical and Computer Engineering, 8(6), 4713-4723. https://doi.org/10.11591/ijece.v8i6.pp4713-4723

Blum, C., Blesa Aguilera, M. J., Roli, A., & Sampels, M. (2008). Hybrid metaheuristics an emerging approach to optimization, Springer, Berlin. https://doi.org/10.1007/978-3-540-78295-7 [+]
Amiri, M., & Mohtashami, A. (2011). Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm. International Journal of Advanced Manufacturing Technology, 62, 371-383. https://doi.org/10.1007/s00170-011-3802-8

Ariyani, A. K., Mahmudy, W. F., & Anggodo, Y. P. (2018). Hybrid genetic algorithms and simulated annealing for multi-trip vehicle routing problem with time windows. International Journal of Electrical and Computer Engineering, 8(6), 4713-4723. https://doi.org/10.11591/ijece.v8i6.pp4713-4723

Blum, C., Blesa Aguilera, M. J., Roli, A., & Sampels, M. (2008). Hybrid metaheuristics an emerging approach to optimization, Springer, Berlin. https://doi.org/10.1007/978-3-540-78295-7

Costa, A., Alfieri, A., Matta, A., & Fichera, S. (2015). A parallel tabu search for solving the primal buffer allocation problem in serial production systems. Computers & Operations Research, 97-112. https://doi.org/10.1016/j.cor.2015.05.013

Cruz, F. R., Kendall, G., While, L., Duarte, A. R., & Brito, N. L. (2012). Throughput maximization of queueing networks with simultaneous minimization of servicer rates and buffers. Mathematical Problems in Engineering, 1-19. https://doi.org/10.1155/2012/692593

Curry, G., & Feldman, R. (2009). Manufacturing Systems Modeling and Analysis, Springer, Berlin.

Demir, L., Tunali, S., & Tursel Eliiyi, D. (2014). The state of the art on buffer allocation problem: a comprehensive survey. Journal of Intelligent Manufacturing, 25(3), 371-392. https://doi.org/10.1007/s10845-012-0687-9

Demir, L., & Tunali, S. (2008). A new approach for optimal buffer allocation in unreliable production lines. Pcoceedings of 38th International Conference on Computers, (págs. 1962-1970).

Dolgui, A., Eremeev, A. V., & Sigaev, V. S. (2007). HBBA: hybrid algorithm for buffer allocation in tandem production lines. Journal of Intelligent Manufacturing, 18, 411-420. https://doi.org/10.1007/s10845-007-0030-z

Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning (Primera ed.), Addison-Wesley Professional, United States of America.

Gutiérrez Pulido, H., & De la Vara Salazar, R. (2012). Análisis y diseño de experimentos (Tercera ed.), McGraw-Hill, México.

Huilcapi, V., Lima, B., Blasco, X., & Herrero, J. M. (2018). Multi-objective optimization in modeling and control for rotary inverted pendulum. Revista Iberoamericana de Automática e Informática Industrial, 15(4), 363-373. https://doi.org/10.4995/riai.2018.8739

Kose, S. Y., & Kilincci, O. (2015). Hybrid approach for buffer allocation in open serial production lines. Computers & Operations Research, 60, 67-78. https://doi.org/10.1016/j.cor.2015.01.009

Kose, S. Y., & Kilincci, O. (2018). A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-018-1435-6

Liu, C., & Tu, F. S. (1994). Buffer allocation via the genetic algorithm. In: Proceedings of 33rd conference on decision and control, 609-610.

Mohtashami, A. (2014). A new hybrid method for buffer sizing and machine allocation in unreliable production and assembly lines with general distribution time-dependent parameters. International Journal of Advanced Manufacturing Technology, 74, 1577-1593. https://doi.org/10.1007/s00170-014-6098-7

Nahas, N., & Nourelfath, M. (2018). Joint optimization of maintenance, buffers and machines in manufacturing lines. Engineering Optimization, 50(1), 37-54. https://doi.org/10.1080/0305215X.2017.1299716

Nahas, N., Nourelfath, M., & Ait-Kadi, D. (2009). Selecting machines and buffers in unreliable series-parallel production lines. International Journal of Production Research, 47(14), 3741-3774. https://doi.org/10.1080/00207540701806883

Nahas, N., Nourelfath, M., & Gendreau, M. (2014). Selecting machines and buffers in unreliable assembly/disassembly manufacturing networks. International Journal of Production Economics, 154, 113-126. https://doi.org/10.1016/j.ijpe.2014.04.011

Narasimhamu, K. L., Reddy, V. V., & Rao, C. (2014). Optimal buffer allocation in tandem closed queuing network with single server using PSO. Procedia Materials Science, 5, 2084-2089. https://doi.org/10.1016/j.mspro.2014.07.543

Narasimhamu, K. L., Reddy, V. V., & Rao, C. (2015). Optimization of buffer allocation in manufacturing system using particle swarm optimization. International Review on Modelling and Simulations, 8(2). https://doi.org/10.15866/iremos.v8i2.5666

Ortiz-Quisbert, M. E., Duarte-Mermoud, M. A., Milla, F., & Castro-Linares, R. (2016). Fractional adaptive control optimized by genetic algorithms, applied to automatic voltage regulators. Revista Iberoamericana de Automática e Informática industrial, 13(4), 403-409. https://doi.org/10.1016/j.riai.2016.07.004

Papadopoulos, C. T., O'Kelly, M. E., Vidalis, M. J., & Spinellis, D. (2009). Analysis and design of discrete part production lines. New York: Springer. https://doi.org/10.1007/978-0-387-89494-2_2

Papadopoulos, H. T., & Vidalis, M. I. (2001). Minimizing WIP inventory in reliable production lines. International Journal of Production Economics, 70, 185-197. https://doi.org/10.1016/S0925-5273(00)00056-6

Rodríguez-Blanco, T., Sarabia, D., & De Prada, C. (2018). Real-time optimization using the modifier adaptation methodology. Revista Iberoamericana de Automática e Informática industrial, 15(2), 133-144. https://doi.org/10.4995/riai.2017.8846

Shi, L., & Men, S. (2003). Optimal buffer allocation in production lines. IIE Transactions, 35, 1-10. https://doi.org/10.1080/07408170304431

Shortle, J., Thompson, J., Gross, D., & Harris, C. (2018). Fundamentals of Queueing Theory (Fifth ed.), Wiley, United States of America. https://doi.org/10.1002/9781119453765

Spinellis, D. D., & Papadopoulos, C. T. (2000a). A simulated annealing approach for buffer allocation in reliable production lines. Annals of Operations Research, 93, 373-384. https://doi.org/10.1023/A:1018984125703

Spinellis, D. D., & Papadopoulos, C. T. (2000b). Stochastic algorithms for buffer allocation in reliable production lines. Mathematical Problems in Engineering, 5, 441-458. https://doi.org/10.1155/S1024123X99001180

Spinellis, D., Papadopoulos, C., & Smith, J. M. (2000). Large production line optimisation using simulated annealing. International Journal of Production Research, 38(3), 509-541. https://doi.org/10.1080/002075400189284

Su, C., Shi, Y., & Dou, J. (2017). Multi-objective optimization of buffer allocation for remanufacturing system based on TS-NSGAII hybrid algorithm. Journal of Cleaner Production, 166, 756-770. https://doi.org/10.1016/j.jclepro.2017.08.064

Takahashi, Y., Miyahara, H., & Hasegawa, T. (1980). An approximation method for open restricted queueing networks. Operations Research, 28(3), 594-602. https://doi.org/10.1287/opre.28.3.594

Vergara, H. A., & Kim, D. S. (2009). A new method for the placement of buffers in serial production lines. International Journal of Production Research, 47(16), 4437-445. https://doi.org/10.1080/00207540801939022

Wei, H., Li, S., Jiang, H., Hu, J., & Hu, J. (2018). Hybrid genetic simulated annealing algorithm for improved flow shop scheduling with makespan criterion. Applied Sciences, 8(2621), 1-20. https://doi.org/10.3390/app8122621

Weiss, S., Schwarz, J. A., & Stolletz, R. (2018). The buffer allocation problem in production lines: Formulations, solution methods, and instances. IISE Transactions. https://doi.org/10.1080/24725854.2018.1442031

[-]

This item appears in the following Collection(s)

Show full item record