Aplicación de la Búsqueda Armónica para el problema de formación de celdas de manufactura

Resumen

Introducción: La manufactura celular (MC) es una aplicación de la tecnología de grupos que consiste en la agrupación de familias de productos y la formación de familias de máquinas, mediante la descomposición de un sistema de manufactura complejo en subsistemas que atienden las operaciones de familias enteras de productos. Durante el presente trabajo se desarrolla un modelo de programación lineal entera que integra costos de producción con costos por transferencias entre celdas, además, se propone como método de solución un algoritmo denominado Búsqueda Armónica

Objetivo: Determinar el desempeño de la Búsqueda Armónica modificada y las variantes de asignación de máquinas al problema de formación de celdas de manufactura.

Metodología: Se desarrolla un modelo matemático de programación entera, el cual utiliza variables binarias para determinar la asignación de las operaciones de diversos productos a distintas máquinas en diferentes celdas, y variables enteras para cuantificar los requerimientos de máquinas y la cantidad de transferencias entre celdas. La validación del modelo se hace utilizando instancias modificadas de la literatura en el software GAMS usando el solver CPLEX y se desarrolla en MATLAB el algoritmo metaheurístico para dar solución aproximada.

Resultados: Se encuentra que las variantes propuestas integradas en la Búsqueda Armónica logran buenos resultados aprovechando el enfoque de explotación del espacio de búsqueda.

Conclusiones: A partir de las variantes aplicadas se logró encontrar muy buenas soluciones en tiempos considerablemente cortos; no obstante, es necesario implementar estrategias de exploración del espacio de búsqueda con el fin de evitar caer en óptimos locales.

Palabras clave: Búsqueda Armónica, Diseño de Plantas, Manufactura Celular, Metaheurísticas

Referencias

R. Kumar, S. P. Singh, and K. Lamba, "CO," no. September, 2018.

S. S. Heragu, "Group technology and cellular manufacturing," IEEE Trans. Syst. Man. Cybern., vol. 24, no. 2, pp. 203-215, 1994. https://doi.org/10.1109/21.281420

A. I. A. I. Abduelmola and S. M. S. M. S. Taboun, "A simulated annealing algorithm for designing cellular manufacturing systems with productivity consideration," Prod. Plan. Control, vol. 11, no. 6, pp. 589-597, Jan. 2000. https://doi.org/10.1080/095372800414151

N. L. Hyer and K. A. Brown, "Discipline of real cells," J. Oper. Manag., vol. 17, no. 5, pp. 557-574, 1999. https://doi.org/10.1016/S0272-6963(99)00003-0

J. Wang and C. Roze, "Formation of machine cells and part families: A modified p-median model and a comparative study," Int. J. Prod. Res., vol. 35, no. 5, pp. 1259-1286, May 1997. https://doi.org/10.1080/002075497195317

A. Kusiak and W. S. Chow, "Decomposition of manufacturing systems," IEEE J. Robot. Autom., vol. 4, no. 5, pp. 457-471, 1988. https://doi.org/10.1109/56.20430

A. Mungwattana, "Design of cellular manufacturing systems for dynamic and uncertain production requirements with presence of routing flexibility," ProQuest Diss. Theses, p. 233 p., 2000.

N. Singh, "Design of cellular manufacturing systems: An invited review," Eur. J. Oper. Res., vol. 69, no. 3, pp. 284-291, Sep. 1993. https://doi.org/10.1016/0377-2217(93)90016-G

Z. W. Geem, Music-inspired harmony search algorithm: theory and applications. Springer Verlag. Springer, 2009. https://doi.org/10.1007/978-3-642-00185-7

Y. Li, X. Li, and J. N. D. Gupta, "Expert Systems with Applications Solving the multi-objective flowline manufacturing cell scheduling problem by hybrid harmony search," Expert Syst. Appl., vol. 42, no. 3, pp. 1409-1417, 2015. https://doi.org/10.1016/j.eswa.2014.09.007

K. Z. Gao, P. N. Suganthan, Q. K. Pan, T. J. Chua, T. X. Cai, and C. S. Chong, "Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling," Inf. Sci. (Ny)., vol. 289, pp. 76-90, 2014. https://doi.org/10.1016/j.ins.2014.07.039

T. X. C. C. S. Chong, "Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives," J. Intell. Manuf., pp. 363-374, 2016.

K. Nekooei, M. M. Farsangi, H. Nezamabadi-pour, and K. Y. Lee, "An Improved Multi-Objective Harmony Search for Optimal Placement of DGs in Distribution Systems," IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 557-567, 2013. https://doi.org/10.1109/TSG.2012.2237420

J. R. King and V. Nakornchai, "Machine-component group formation in group technology: review and extension," Int. J. Prod. Res., vol. 20, no. 2, pp. 117-133, Apr. 2007. https://doi.org/10.1080/00207548208947754

J. R. King, "Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm," Int. J. Prod. Res., vol. 18, no. 2, pp. 213-232, Apr. 1980. https://doi.org/10.1080/00207548008919662

H. Seifoddini and B. Tjahjana, "Part-family formation for cellular manufacturing: A case study at Harnischfeger," Int. J. Prod. Res., vol. 37, no. 14, pp. 3263-3273, Sep. 1999. https://doi.org/10.1080/002075499190275

C. DIMOPOULUS and N. MORT, "Evolving similarity coefficients for the solution of cellular manufacturing problems," Proc. Congr. Evol. Comput. CEC 2000, pp. 617-624, 2000.

J. McAuley, "Machine grouping for efficient production," Prod. Eng., vol. 51, no. 2, p. 53, Feb. 1972. https://doi.org/10.1049/tpe.1972.0006

H. Seifoddini and P. M. Wolfe, "Application of the Similarity Coefficient Method in Group Technology," IIE Trans., vol. 18, no. 3, pp. 271-277, Sep. 1986. https://doi.org/10.1080/07408178608974704

G. Srinivasan and T. T. Narendran, "GRAFICS-a nonhierarchical clustering algorithm for group technology," Int. J. Prod. Res., vol. 29, no. 3, pp. 463-478, Mar. 1991. https://doi.org/10.1080/00207549108930083

M. Chandrasekharan and R. Rajagopalan, "ZODIAC-an algorithm for concurrent formation of part-families and machine-cells," Int. J. Prod. Res., vol. 25, no. 6, pp. 835-850, Jun. 1987. https://doi.org/10.1080/00207548708919880

M. Chandrasekharan and R. Rajagopalan, "An ideal seed non-hierarchical clustering algorithm for cellular manufacturing," Int. J. Prod. Res., vol. 24, no. 2, pp. 451-463, Mar. 1986. https://doi.org/10.1080/00207548608919741

A. Kusiak, "The generalized group technology concept," Int. J. Prod. Res., vol. 25, no. 4, pp. 561-569, Apr. 1987. https://doi.org/10.1080/00207548708919861

A. P. Sergio Nicoletti, Gaia Nicosia, "Group Technology with Flow Shop Cells," Università Degli Studi Di Roma Tre. Dipartimento di Informática e Automazzione, vol. 8. 1998.

Z. Y. Lim, S. G. Ponnambalam, and K. Izui, "Multi-objective hybrid algorithms for layout optimization in multi-robot cellular manufacturing systems," Knowledge-Based Syst., vol. 120, pp. 87-98, Mar. 2017. https://doi.org/10.1016/j.knosys.2016.12.026

M. Diaby and A. L. Nsakanda, "Large-scale capacitated part-routing in the presence of process and routing flexibilities and setup costs," J. Oper. Res. Soc., vol. 57, no. 9, pp. 1100-1112, Sep. 2006. https://doi.org/10.1057/palgrave.jors.2602072

H. Djellab and M. Gourgand, "A new heuristic procedure for the single-row facility layout problem," Int. J. Comput. Integr. Manuf., vol. 14, no. 3, pp. 270-280, Jan. 2001. https://doi.org/10.1080/09511920010020721

M. Z. Allahyari and A. Azab, "A Novel Bi-level Continuous Formulation for the Cellular Manufacturing System Facility Layout Problem," Procedia CIRP, vol. 33, pp. 87-92, 2015. https://doi.org/10.1016/j.procir.2015.06.017

S. P. Darla, C. D. Naiju, and P. V. Sagar, "Optimization of Inter Cellular Movement of Parts in Cellular Manufacturing System Using Genetic Algorithm Optimization of Inter Cellular Movement of Parts in Cellular Manufacturing System Using Genetic Algorithm," no. January, 2014. https://doi.org/10.19026/rjaset.7.235

M. Aghajani, A. Keramati, and R. T. Moghadam, "A mathematical programming model for cellular manufacturing system controlled by kanban with rework consideration," pp. 1377-1394, 2016. https://doi.org/10.1007/s00170-015-7635-8

Y. B. Sahin and S. Alpay, "A metaheuristic approach for a cubic cell formation problem," Expert Syst. Appl., vol. 65, pp. 40-51, 2016. https://doi.org/10.1016/j.eswa.2016.08.034

S. S. E. Teymourian, "New approach based on group technology for the consolidation problem in cloud computing-mathematical model and genetic algorithm," Comput. Appl. Math., vol. 37, no. 1, pp. 693-718, 2018. https://doi.org/10.1007/s40314-016-0362-4

R. Maleki, S. Ketabi, and F. M. Rafiei, "Grouping both machines and parts in cellular technology by Genetic Algorithm," J. Ind. Prod. Eng., vol. 1015, pp. 1-11, 2018.

H. Feng, T. Xia, W. Da, L. Xi, and E. Pan, "Concurrent design of cell formation and scheduling with consideration of duplicate machines and alternative process routings," J. Intell. Manuf., vol. 30, no. 1, pp. 275-289, 2019. https://doi.org/10.1007/s10845-016-1245-7

V. Jayakumar and J. Raju, "A Simulated Annealing Algorithm for Machine Cell Formation Under Uncertain Production Requirements," pp. 7345-7354, 2014. https://doi.org/10.1007/s13369-014-1306-1

C. Liu and J. Wang, "Cell formation and task scheduling considering multi-functional resource and part movement using hybrid simulated annealing," Int. J. Comput. Intell. Syst., vol. 9, no. 4, pp. 765-777, 2016. https://doi.org/10.1080/18756891.2016.1204123

F. Shafigh, F. M. Defersha, and S. Eid, "A linear programming embedded simulated annealing in the design of distributed layout with production planning and systems reconfiguration," Int. J. Adv. Manuf. Technol., pp. 1119-1140, 2017. https://doi.org/10.1007/s00170-016-8813-z

A. Iqbal and K. A. Al-Ghamdi, "Energy-efficient cellular manufacturing system: Eco-friendly revamping of machine shop configuration," Energy, vol. 163, pp. 863-872, 2018. https://doi.org/10.1016/j.energy.2018.08.168

Y. Gholipour-kanani, R. Tavakkoli-moghaddam, and A. Khorrami, "Solving a multi-criteria group scheduling problem for a cellular manufacturing system by scatter search," vol. 669, 2011. https://doi.org/10.1080/10170669.2010.549663

M. S. Jabal-ameli and M. Moshref-javadi, "Concurrent cell formation and layout design using scatter search," pp. 1-22, 2014. https://doi.org/10.1007/s00170-013-5342-x

A. S. Amiri and R. Ghodsi, "A variable neighborhood search method for an integrated cellular manufacturing systems with production planning and system reconfiguration," AMS2010 Asia Model. Symp. 2010 - 4th Int. Conf. Math. Model. Comput. Simul., pp. 181-186, 2010.

F. Jolai, M. Taghipour, and B. Javadi, "A variable neighborhood binary particle swarm algorithm for cell layout problem," pp. 327-339, 2011. https://doi.org/10.1007/s00170-010-3039-y

S. Chung, T. Wu, and C. Chang, "An efficient tabu search algorithm to the cell formation problem with alternative routings and machine reliability considerations q," Comput. Ind. Eng., vol. 60, no. 1, pp. 7-15, 2011. https://doi.org/10.1016/j.cie.2010.08.016

J. Du, G. Wang, Y. Yan, and Q. Sang, "Tabu Search-based Formation of Reconfigurable Manufacturing Cells Jingjun Du 1," Appl. Mech. an Mater., vol. 400, no. 1, pp. 34-41, 2013. https://doi.org/10.4028/www.scientific.net/AMM.397-400.34

F. Sarayloo and R. Tavakkoli-Moghaddam, "Multi Objective Particle Swarm Optimization for a Dynamic Cell Formation Problem," World Congr. Eng., vol. 3, 2010.

A. Azadeh, S. Pashapour, and S. Abdolhossein Zadeh, "Designing a cellular manufacturing system considering decision style, skill and job security by NSGA-II and response surface methodology," Int. J. Prod. Res., vol. 54, no. 22, pp. 6825-6847, 2016. https://doi.org/10.1080/00207543.2016.1178407

K. S. Lee and Z. W. Geem, "A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice," Comput. Methods Appl. Mech. Eng., vol. 194, no. 36-38, pp. 3902-3933, Sep. 2005. https://doi.org/10.1016/j.cma.2004.09.007

J. Arkat, M. H. Farahani, and F. Ahmadizar, "Multi-objective genetic algorithm for cell formation problem considering cellular layout and operations scheduling," Int. J. Comput. Integr. Manuf., vol. 25, no. 7, pp. 625-635, Jul. 2012. https://doi.org/10.1080/0951192X.2012.665182

M. Solimanpur, P. Vrat, and R. Shankar, "Ant colony optimization algorithm to the inter-cell layout problem in cellular manufacturing," Eur. J. Oper. Res., vol. 157, no. 3, pp. 592-606, Sep. 2004. https://doi.org/10.1016/S0377-2217(03)00248-0

A. J. Vakharia and Y. L. Chang, "Cell formation in group technology: A combinatorial search approach," Int. J. Prod. Res., vol. 35, no. 7, pp. 2025-2044, 1997. https://doi.org/10.1080/002075497195056

B. P. Ahmed, R. Tavakkoli-moghaddam, and N. Safaei, "A comparison of heuristic methods for solving a cellular manufacturing model in a dynamic environment," vol. 44, no. 0, 2004.

F. S. Hillier and G. Lieberman, Introducción a la Investigación de Operaciones. 1997.

Z. Yang, "Analysis and Design of Cellular Manufacturing Systems: Machine-Part Cell Formation and Operation Allocation," Case Western Reserve University / OhioLINK, 1995.

D. M. Himmelblau, Applied Nonlinear Programming, 1st ed. McGraw-Hill, 1972.

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Acerca de los Autores

Edwin Alberto Garavito Hernández, Universidad Industrial de Santander, Bucaramanga, (Colombia)

Edwin Alberto Garavito Hernández obtuvo su título de M.Sc. en Ingeniería Industrial de la Universidad de Puerto Rico Recinto Universitario Mayagüez en 2016. Ha estado vinculado a la Universidad Industrial de Santander como Profesor Tiempo Completo en el área de diseño de sistemas productivos y simulación discreta. Entre sus intereses de investigación están: optimización, métodos heurísticos, gestión de la producción, diseño de sistemas productivos, simulación, entre otros. https://orcid.org/0000-0002-0145-232X

Leonardo Hernán Talero Sarmiento, Universidad Industrial de Santander, Bucaramanga, (Colombia)

Leonardo Hernán Talero Sarmiento Obtuvo su título de M.Sc. en Ingeniería Industrial de la Universidad Industrial de Santander, Colombia en 2018. Ha estado vinculado a la Universidad Industrial de Santander como becario en investigación en el grupo OPALO. Sus intereses de investigación son gestión de la producción, finanzas, heurísticas y el análisis de modelos de causalidad en talento humano. https://orcid.org/0000-0002-4129-9163

Laura Yeraldín Escobar Rodríguez, Universidad Industrial de Santander, Bucaramanga, (Colombia)

Laura Yeraldín Escobar Rodríguez obtuvo su título en Ingeniería Industrial de la Universidad Industrial de Santander, Colombia en 2018. Está vinculada a la Universidad Industrial de Santander como becaria en investigación en el grupo OPALO. Sus intereses de investigación son Diseño de Sistemas Productivos, Gestión de la Producción, optimización y métodos heurísticos. https://orcid.org/0000-0003-3350-9113

Publicado
2019-12-06
Cómo citar
Garavito Hernández, E., Talero Sarmiento, L., & Escobar Rodríguez, L. (2019). Aplicación de la Búsqueda Armónica para el problema de formación de celdas de manufactura. INGE CUC, 15(2). https://doi.org/10.17981/ingecuc.15.2.2019.15