Artículos
Desarrollo de un algoritmo genético para el diseño de sistemas de manufactura celular a partir de una nueva función de aptitud
Publicado 2007-10-19
Palabras clave
- Celdas de Fabricación,
- tecnología de grupos,
- manufactura celular,
- algoritmos genéticos
Cómo citar
Ortiz Pimiento, N. R., & Gómez Gómez, S. (2007). Desarrollo de un algoritmo genético para el diseño de sistemas de manufactura celular a partir de una nueva función de aptitud. Revista UIS Ingenierías, 6(2), 71–83. Recuperado a partir de https://revistas.uis.edu.co/index.php/revistauisingenierias/article/view/411
Resumen
Este artículo desarrolla un algoritmo genético a través del cual es posible obtener una solución factible y satisfactoria al problema de conformación de celdas de manufactura. El algoritmo genético propuesto incluye un nuevo planteamiento de la función de aptitud tradicionalmente empleada para resolver este problema, permitiendo obtener una solución más ajustada a la realidad. Para validar el esquema y los operadores genéticos diseñados, se presenta un ejemplo de aplicación en donde se supone la existencia de una empresa que desea organizar de una manera efciente cuatro celdas de trabajo, teniendo en cuenta la fabricación de 30 productos diferentes en 10 tipos de máquina.
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N. Morad and A. Zalzala. “Formulations for Cellular Manufacturing and Batch Scheduling Using Genetic
Algorithms”. UKACC International Conference on CONTROL, Conference Publication, No. 427, 1996, pp.473- 478.
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Re-aligning research objectives in Cellular Manufacturing System Design: A User’s perspective. Available: http://www.iimb.ernet.in/~mahadev/cmsurvey.pdf [citado 20 de septiembre de 2007].
X. Wu, C. Chu, Y. Wang and W. Yang, “A Genetic Algorithm for Integrated Cell Formation and Layout Decisions”, IEEE 0-7803-7282-4, 2002, pp. 1866-1872.
ABDUELMOLA, A.I. Modelling of Cellular Manufacturing Systems with Productivity Considerations: a Simulated Annealing algorithm. [PhD Thesis]. Windsor, Canadá, University of Windsor, 2000.
MUNGWATANNA, A. Design of Cellular Manufacturing Systems for Dynamic and Uncertain Production requirements with Presence of Routing Flexibility. [PhD Thesis]. Blacksburg, Estados Unidos: Virginia Polytechnic Institute and State University, 2000.
J. Wang and C. Roze. “Formation of machine cells and part families: a modifed p-median model and a comparative study”. International Journal of Production Research, Vol. 35, No. 5, May 1997, pp. 1259-1286.
S. Heragu. “Group technology and cellular manufacturing”, Transactions on systems, man, and cybernetics, Vol. 24, No. 2, February 1994, pp. 203-215.
J. R. King and V. Nakornchai. “Machine-component group formation in group technology: review and extension”. International Journal of Production Research. Vol. 20, No. 2, 1982, pp. 117.
A. Kusiak and W. Chow. “Decomposition of Manufacturing Systems”. IEEE, Journal of robotics and automation. Vol. 4, No. 5, 1988, pp. 457.
N. Singh. “Design of cellular manufacturing systems: An invited review”. European Journal of Operational
Research, Vol. 69, September 1993, pp. 284–291.
S. Heragu. “Group technology and cellular manufacturing”, Transactions on systems, man, and cybernetics, Vol. 24, No. 2, February 1994, pp. 205.
A. Ballakur and H. Steudel. “A Within-Cell Utilization Based Heuristic for Designing Cellular Manufacturing
Systems”. International Journal of Production Research, Vol. 25, No. 5, May 1987, pp. 639-665.
J. McAuley. “Machine grouping for efficient production”. The Production Engineer. Vol. 51, 1972, pp.53-57.
H. Seifoddini and B. Tjahjana. “Part-Family Formation for Cellular Manufacturing: A Case Study at Harnischfeger”. International Journal of Production Research, Vol. 37, No. 14, September 1999, pp.3262-3273.
C. T. Mosier. “An experiment investigating the application of clustering procedures and similarity coeffcient to the GT machine cell formation problem”. International Journal of Production Research, Vol. 27, October 1989, pp. 1811-1835.
M. P. Chandrasekharan and R. Rajagopalan. “An ideal seed non-hierarchical clustering algorithm for cellular manufacturing”. International Journal of Production Research. Vol. 24, No. 2, 1986, pp. 451-464.
M. P. Chandrasekharan and R. Rajagopalan. “ZODIAC: An algorithm for concurrent formation of
part families and machine cells”. International Journal of Production Research, Vol. 25, No. 6, June 1987, pp.835-850.
G. Srinivasa and T. Narendran. “GRAFICS – a non hierarchical clustering algorithm for group technology”.
International Journal of Production Research, Vol. 29, No. 3, March 1991, pp. 463-478.
P. H. Waghodekar and S. Sahu. “Machinecomponent cell formation in group technology: MACE”. International Journal of Production Research, Vol. 22, No. 6 November 1984, pp. 937-948.
Group Technology with Flow Shop Cells. Available: http://web.dia.uniroma3. it/ricerca/rapporti/rt/1998-33.
pdf . [citado 20 de septiembre de 2007].
Approaches to the General Cell Formation Problem. Available: https://dspace.lboro.ac.uk/dspace/handle/2134/2027 . [citado 20 de septiembre de 2007].
An Integrated Formulation of Manufacturing Cell Formation with Capacity Planning and Multiple Routings. Available: http://www.acsu.buffalo.edu/ ~nagi/pubs/annor.pdf. [20 de septiembre de 2007].
C. Dimopoulos. “Explicit consideration of multiple objectives in cellular manufacturing”. Engineering
Optimization. Vol. 39, No. 5, July 2007, pp. 551–565.
Y. B. Moon and S. C. CHI. “Generalized Part Family Formation Using Neural Network Techniques”. Journal
of Manufacturing Systems, Vol. 11, No. 3, January 1992, pp. 149-159.
S. C. Chi and S. Y. Liu. “A Flexible Neural Network Approach for Machine Cell Formation”. IEEE, 0-7803-2559-1, 1995, pp. 2064-2069.
Z. Yang. Analysis and Design of Cellular Manufacturing Systems: Machine-Part Cell Formation and operation Allocation. [PhD Thesis]. Cleveland, United States. Case Western Reserve University, 1995.
N. C. Suresh, J. Slomp and S. Kaparthi. “Sequence dependent clustering of parts and machines: a Fuzzy
ART neural network approach”. International Journal of Production Research. Vol. 37, No. 12, August 1999, pp.2793-2816.
C. C. Tsai, C. H. Chu and T. A. Barta. “Modelling and analysis of manufacturing cell formation problem with fuzzy mixed-integer programming”. IIE Transactions, Vol. 29, July 1997, pp. 533-547.
A new fuzzy-c-means and assignment-techniquebased cell formation algorithm to perform part-typeclusters and machine-type-clusters. Available: http://public.rz.fh-wolfenbuettel. de/~hoeppnef/bib/paper/Susanto-PPC-10-4.pdf. [citado 20 de septiembre de 2007].
J. Li, C. Chu, Y. Wang and W. Yan. “An Improved Fuzzy C-Means Algorithm for Manufacturing Cell
Formation”. IEEE 0-7803-7280-8, 2002, pp. 1505-1510.
S. Lee and H. P. Wang. “Manufacturing cell formation: A dual-objective simulated annealing approach”.
International Journal of Advanced Manufacturing Technology, Vol. 7, October 1992, pp.: 314-320.
A Comparison of Heuristic Methods for Solving a Cellular Manufacturing Model in a Dynamic Environment. Available: http://www.wlv.ac.uk/PDF/uwbs_04%20WP007-04%20Ahmed%20 et%20al.pdf [citado20 de septiembre de 2007].
C. H. Chu and C. C. Tsai. “A Heuristic Genetic Algorithm for Grouping Manufacturing Cells”. IEEE,
0-7803-6657-3, 2001, pp. 310-317.
C. Dimopoulos and A Zalzala. “Optimization of Cell Confguration and Comparisons using Evolutionary Computation Approaches”. IEEE 0-7803-4869-9, 1998, pp. 148-153.
N. Morad and A. Zalzala. “Formulations for Cellular Manufacturing and Batch Scheduling Using Genetic
Algorithms”. UKACC International Conference on CONTROL, Conference Publication, No. 427, 1996, pp.473- 478.
A. J. Vakharia and Y. L. Chang. “Cell formation in group technology: a combinatorial search approach”. International Journal of Production Research. Vol. 35, No. 7, July 1997, pp. 2025-2043.
Gomez S, Cervantes M, Ortiz N. Formulación y Evaluación de un modelo heurístico para el diseño de sistemas de manufactura celular mediante la implementación de algoritmos genéticos. [Trabajo de Grado]. Bucaramanga, Colombia, Universidad Industrial de Santander. 2007.