IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v102y2006i1p1-21.html
   My bibliography  Save this article

A group genetic algorithm for the machine cell formation problem

Author

Listed:
  • Vila Goncalves Filho, Eduardo
  • Jose Tiberti, Alexandre

Abstract

No abstract is available for this item.

Suggested Citation

  • Vila Goncalves Filho, Eduardo & Jose Tiberti, Alexandre, 2006. "A group genetic algorithm for the machine cell formation problem," International Journal of Production Economics, Elsevier, vol. 102(1), pages 1-21, July.
  • Handle: RePEc:eee:proeco:v:102:y:2006:i:1:p:1-21
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925-5273(05)00055-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Plaquin, Marie-France & Pierreval, Henri, 2000. "Cell formation using evolutionary algorithms with certain constraints," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 267-278, March.
    2. Uddin, Muhammad Kutub & Shanker, Kripa, 2002. "Grouping of parts and machines in presence of alternative process routes by genetic algorithm," International Journal of Production Economics, Elsevier, vol. 76(3), pages 219-228, April.
    3. De Lit, P. & Falkenauer, E. & Delchambre, A., 2000. "Grouping genetic algorithms: an efficient method to solve the cell formation problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 51(3), pages 257-271.
    4. Balakrishnan, Jaydeep & Cheng, Chun Hung & Conway, Daniel G. & Lau, Chun Ming, 2003. "A hybrid genetic algorithm for the dynamic plant layout problem," International Journal of Production Economics, Elsevier, vol. 86(2), pages 107-120, November.
    5. Gravel, Marc & Luntala Nsakanda, Aaron & Price, Wilson, 1998. "Efficient solutions to the cell-formation problem with multiple routings via a double-loop genetic algorithm," European Journal of Operational Research, Elsevier, vol. 109(2), pages 286-298, September.
    6. Moon, Chiung & Gen, Mitsuo, 1999. "A genetic algorithm-based approach for design of independent manufacturing cells," International Journal of Production Economics, Elsevier, vol. 60(1), pages 421-426, April.
    7. Gong, Dijin & Yamazaki, Genji & Gen, Mitsuo & Xu, Weixuan, 1999. "A genetic algorithm method for one-dimensional machine location problems," International Journal of Production Economics, Elsevier, vol. 60(1), pages 337-342, April.
    8. Kar Yan Tam, 1992. "Genetic algorithms, function optimization, and facility layout design," European Journal of Operational Research, Elsevier, vol. 63(2), pages 322-346, December.
    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. Wu, Tai-Hsi & Chung, Shu-Hsing & Chang, Chin-Chih, 2010. "A water flow-like algorithm for manufacturing cell formation problems," European Journal of Operational Research, Elsevier, vol. 205(2), pages 346-360, September.
    2. Solimanpur, Maghsud & Elmi, Atabak, 2013. "A tabu search approach for cell scheduling problem with makespan criterion," International Journal of Production Economics, Elsevier, vol. 141(2), pages 639-645.
    3. Rym Ben Bachouch & Jihène Tounsi & Chouari Borhen, 2020. "Home health care scheduling activities," Post-Print hal-03229580, HAL.
    4. Angra, Surjit & Sehgal, Rakesh & Samsudeen Noori, Z., 2008. "Cellular manufacturing--A time-based analysis to the layout problem," International Journal of Production Economics, Elsevier, vol. 112(1), pages 427-438, March.
    5. Dmitry Krushinsky & Boris Goldengorin, 2012. "An exact model for cell formation in group technology," Computational Management Science, Springer, vol. 9(3), pages 323-338, August.

    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. Hicks, Christian, 2006. "A Genetic Algorithm tool for optimising cellular or functional layouts in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 104(2), pages 598-614, December.
    2. Nearchou, Andreas C., 2006. "Meta-heuristics from nature for the loop layout design problem," International Journal of Production Economics, Elsevier, vol. 101(2), pages 312-328, June.
    3. Loiola, Eliane Maria & de Abreu, Nair Maria Maia & Boaventura-Netto, Paulo Oswaldo & Hahn, Peter & Querido, Tania, 2007. "A survey for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 176(2), pages 657-690, January.
    4. Ioannou, George, 2006. "Time-phased creation of hybrid manufacturing systems," International Journal of Production Economics, Elsevier, vol. 102(2), pages 183-198, August.
    5. Solimanpur, M. & Vrat, Prem & Shankar, Ravi, 2004. "A heuristic to minimize makespan of cell scheduling problem," International Journal of Production Economics, Elsevier, vol. 88(3), pages 231-241, April.
    6. Kumar, Akhilesh & Prakash & Tiwari, M.K. & Shankar, Ravi & Baveja, Alok, 2006. "Solving machine-loading problem of a flexible manufacturing system with constraint-based genetic algorithm," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1043-1069, December.
    7. Manoj Kumar Paras & Lichuan Wang & Yan Chen & Antonela Curteza & Rudrajeet Pal & Daniel Ekwall, 2018. "A Sustainable Application Based on Grouping Genetic Algorithm for Modularized Redesign Model in Apparel Reverse Supply Chain," Sustainability, MDPI, vol. 10(9), pages 1-19, August.
    8. Ulusoy, Gunduz & Cebelli, Serkan, 2000. "An equitable approach to the payment scheduling problem in project management," European Journal of Operational Research, Elsevier, vol. 127(2), pages 262-278, December.
    9. Rogers, David F. & Kulkarni, Shailesh S., 2005. "Optimal bivariate clustering and a genetic algorithm with an application in cellular manufacturing," European Journal of Operational Research, Elsevier, vol. 160(2), pages 423-444, January.
    10. Vitayasak, Srisatja & Pongcharoen, Pupong & Hicks, Chris, 2017. "A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm," International Journal of Production Economics, Elsevier, vol. 190(C), pages 146-157.
    11. Gomez, A. & Fernandez, Q. I. & De la Fuente Garcia, D. & Garcia, P. J., 2003. "Using genetic algorithms to resolve layout problems in facilities where there are aisles," International Journal of Production Economics, Elsevier, vol. 84(3), pages 271-282, June.
    12. O’Neill, Sam & Wrigley, Paul & Bagdasar, Ovidiu, 2022. "A mixed-integer linear programming formulation for the modular layout of three-dimensional connected systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 739-754.
    13. Yang, Miin-Shen & Hung, Wen-Liang & Cheng, Fu-Chou, 2006. "Mixed-variable fuzzy clustering approach to part family and machine cell formation for GT applications," International Journal of Production Economics, Elsevier, vol. 103(1), pages 185-198, September.
    14. Anjos, Miguel F. & Vieira, Manuel V.C., 2017. "Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions," European Journal of Operational Research, Elsevier, vol. 261(1), pages 1-16.
    15. Jankovits, Ibolya & Luo, Chaomin & Anjos, Miguel F. & Vannelli, Anthony, 2011. "A convex optimisation framework for the unequal-areas facility layout problem," European Journal of Operational Research, Elsevier, vol. 214(2), pages 199-215, October.
    16. Feng, Yanling & Li, Guo & Sethi, Suresh P., 2018. "A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing," International Journal of Production Economics, Elsevier, vol. 196(C), pages 269-283.
    17. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    18. Cornejo-Bueno, L. & Nieto-Borge, J.C. & García-Díaz, P. & Rodríguez, G. & Salcedo-Sanz, S., 2016. "Significant wave height and energy flux prediction for marine energy applications: A grouping genetic algorithm – Extreme Learning Machine approach," Renewable Energy, Elsevier, vol. 97(C), pages 380-389.
    19. Arzi, Yohanan & Bukchin, Joseph & Masin, Michael, 2001. "An efficiency frontier approach for the design of cellular manufacturing systems in a lumpy demand environment," European Journal of Operational Research, Elsevier, vol. 134(2), pages 346-364, October.
    20. Salcedo-Sanz, Sancho & Deo, Ravinesh C. & Cornejo-Bueno, Laura & Camacho-Gómez, Carlos & Ghimire, Sujan, 2018. "An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia," Applied Energy, Elsevier, vol. 209(C), pages 79-94.

    More about this item

    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:eee:proeco:v:102:y:2006:i:1:p:1-21. 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.elsevier.com/locate/ijpe .

    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.