BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Autor
Triki Hager (University of Sfax, Tunisia), Hachicha Wafik (Higher Institute of Industrial Management Sfax, Tunisia), Mellouli Ahmed (University of Sousse, Tunisia), Masmoudi Faouzi (Laboratory Research of Mechanics, Tunisia)
Tytuł
An Assembly Line Balancing Problem Automotive Cables
Źródło
Management and Production Engineering Review, 2015, vol. 6, nr 1, s. 59-66, rys., tab., bibliogr. 27 poz.
Słowa kluczowe
Zarządzanie produkcją, Algorytmy genetyczne
Production management, Genetic algorithms
Uwagi
summ.
Abstrakt
In this paper, an Assembly Line Balancing Problem (ALBP) is presented in a real-world automotive cables manufacturer company. This company found it necessary to balance its line, since it needs to increase the production rate. In this ALBP, the number of stations is known and the objective is to minimize cycle time where both precedence and zoning constrains must be satisfied. This problem is formulated as a binary linear program (BLP). Since this problem is NP-hard, an innovative Genetic Algorithm (GA) is implemented. The full factorial design is used to obtain the better combination GA parameters and a simple convergence experimental study is performed on the stopping criteria to reduce computational time. Comparison of the proposed GA results with CPLEX software shows that, in a reasonable time, the GA generates consistent solutions that are very close to their optimal ones. Therefore, the proposed GA approach is very effective and competitive. (original abstract)
Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. Baybars I., A survey of exact algorithms for the simple assembly line balancing problem, Manag. Sci., 21, 8, 909-932, 1986.
  2. Andre's C., Miralles C., Pastor R., Balancing and scheduling tasks in assembly lines with sequencedependent setup times, European J. of Operat. Resear., 187, 3, 1212-122, 20083.
  3. Kyungchul P., Sungsoo P., Wanhee K., A heuristic for an assembly line balancing problem with incompatibility, range, and partial precedence constraints, Comput. Industrial Engine., 32, 2, 321-332, 1997.
  4. Bautista J., Pereira J., Ant algorithms for a time and space constrained assembly line balancing problem, European J. of Operat. Research., 177, 3, 2016-2032, 2007.
  5. Gao J., Sun L., Wang L., Gen M., An efficient approach for type II robotic assembly line balancing problems, Comput. and Industr. Eng., 56, 3, 1065-1080, 2009.
  6. Gutjahr A.L., Nemhauser G.L., An algorithm for the line balancing problem, Managem. Sc., 11, 2, 308-15, 1964.
  7. Salveson M.E., The assembly line balancing problem, J. of Indus. Engine., 6, 3, 18-25, 1955.
  8. Bowman E.H., Assembly line balancing by linear programming, Operat Resear, 8, 385-389, 1960.
  9. Held M., Karp R.M., Shareshian R., Assembly line balancing dynamic programming with precedence constraints, Operat. Research, 11, 3, 442-459, 1963.
  10. Jackson J.R., A  computing procedure for a line balancing problem, Manag. Science, 2, 3, 261-272, 1956.
  11. Dar-El E.M., Rubinovitch Y., MUST-A multiple solutions technique for balancing single model assembly lines, Manag. Scienc., 25, 11, 1105-1114, 1979.
  12. Peterson C., A tabu search procedure for the simple assembly line balancing problem, In the Proceedings of the Decision Science Institute Conference, Washington, DC, pp. 1502-1504, 1993.
  13. Suresh G., Sahu S., Stochastic assembly line balancing using simulated annealing, Int. J. of Prod. Research, 32, 8, 1801-1810, 1994.
  14. Falkenauer E., Delchambre A ., A genetic algorithm for bin packing and line balancing, In The Proceedings of the 1992 IEEE International Conference on Robotics and Automation, Nice, France, pp. 1189-1192, 1992.
  15. Sabuncuoglu I., Erel E., Tanyer M., Assembly line balancing using genetic algorithms, J. of Intel. Manufact., 11, 3, 295-310, 2000.
  16. Tasan S.O., Tunali S., A review of the current applications of genetic algorithms in assembly line balancing, J. Intel Manufactur., 19, 1, 49-69, 2008.
  17. Goldberg D.Eo., Genetic Algorithms in Search. Optimization and Machine Learning, Addison-Wesley, Reading, MA, 1989.
  18. Liepins G.E., Hilluard M.R., Genetic algorithms: foundations and applications, Annals of Opera. Res., 21, 1, 31-58, 1989.
  19. Aytug H., Khouja M., Vergara F.E., Use of genetic algorithms to solve production and operations management problems: A review, Int. J. of Product. Research, 41, 17, 3955-4009, 2003.
  20. Chan C.C.K., Hui P.C.L., Yeung K.W., Ng F.S.F., Handling the assembly line balancing problem in the clothing industry using a genetic algorithm, Int. J. of Clothing Science and Technol., 10, 1, 21-37, 1998.
  21. Valente S.A., Lopes H.S., Arruda L.V.R., Genetic algorithms for the assembly line balancing problem: A real-world automotive application, Soft Computing and Industry, R. Roy et al. [Eds.], pp. 319-327, 2002.
  22. Leu Y.Y., Matheson L.A., Rees L.P., Assembly line balancing using genetic algorithms with heuristic generated initial populations and multiple criteria, Decision Sciences, 15, 4, 581-606, 1994.
  23. Hamta N., Fatemi Ghomi S.M.T., Jolai F., Bahalke U., Bi-criteria assembly line balancing by considering flexible operation times, Appl. Math. Model, 35, 12, 5592-5608, 2011.
  24. Akpınar S., MiracBayhan G., A hybrid genetic algorithm for mixed model assembly line balancing problem with parallel workstations and zoning constraints, Eng. Appl. of Artificial Intel, 24, 3, 449-457, 2011.
  25. Holland H.J., Adaptation in natural and artificial systems, Ann Arbor. Michigan: The University of Michigan Press, 1975.
  26. Rubinovitz J., Levitin G., Genetic algorithm for assembly line balancing, In J. of Production Economics, 41, 1-3, 343-354, 1995.
  27. Simaria A.S., Vilarinho P.M., A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II, Comput. & Industr. Engin., 47, 4, 391-407, 2004.
Cytowane przez
Pokaż
ISSN
2080-8208
Język
eng
URI / DOI
http://dx.doi.org/10.1515/mper-2015-0008
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu