A binary particle swarm optimization approach to optimize assembly sequence planning
Document Type
Article
Publication Date
1-1-2012
Abstract
This paper presents an approach of applying Binary Particle Swarm Optimization (BPSO) algorithm to an assembly sequence-planning (ASP) problem. Permutation encoding of sequences is used to represent particles, then those particles are strictly subjected to a precedence constraint matrix at which only the feasible sequences will be iterated in the process. An archive is used in storing the feasible sequences and a swap mechanism is used to identify the feasible sequences for iteration. As the nature of assembly sequence planning is a discrete type of problem Binary PSO technique is used.
Keywords
Assembly sequence planning, Particle swarm optimization.
Divisions
fac_eng
Publication Title
Advanced Science Letters
Volume
13
Issue
1
Publisher
Advanced Science Letters
Additional Information
Export Date: 28 January 2013 Source: Scopus Language of Original Document: English Correspondence Address: Mukred, J. A. A.; Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia References: Liu, A., Yang, Y., Xing, Q., Yao, H., Zhang, Y., Zhou, Z., (2011) Adv. Sci. Lett., 4, p. 2180; Lv, H., Lu, C., (2010) Int. J. Adv. Manuf. Technol.; Bourjault, A., (1984), Doc. d'Etat Universite de Franche-Comte, BesanconHomem de Mello, L.S., Sanderson, A.C., (1991) IEEE Trans. Robot. Autom.; Baldwin, D.F., Abell, T.E., Lui, M.-C., de Fazio, T.L., Whitney, D.E., (1991) IEEE Trans. Robot. Autom.; Milner, J.M., Graves, S.C., Whitney, D.E., (1994) Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2058-2063; Wilson, R.H., (1995) IEEE Trans. Robot. Automn., 11, p. 308; Motavalli, S., Islam, A., (1997) Computational Industrial Eng., 32, p. 743; Bonneville, F., Perrard, C., Henrioud, J., (1995) Proceeding of the IEEE Symposium on Emerging Technologies and Factory Automation, 2, pp. 231-239; Sebaaly, M.F., Fujimoto, H., (1996) Japan/USA Symposium on Flexible Automation, 2, p. 1235; Sebaaly, M.F., Fujimoto, H., (2000) IEEE Conference on Evolutionary Computation, 401; de Lit, P., Latinne, P., Rekiek, B., Delchambre, A., (2001) International Journal Production Res., 39, p. 3623; Smith(Chen), S.F., Liu, Y.J., (2002) Journal Industrial Technology, 17; Smith(Chen), S.F., (1998) Proceedings of the 24th ASME Design Automation Conference; Tseng, H.E., Li, J.D., Chang, Y.H., (2004) International Journal Prod. Res., 42, p. 2243; Marian, R.M., Luong, H.S., Abhari, K., (2006) Computational Industrial Eng., 50, p. 503; Failli, F., Dini, G., (2000) Proceedings of the 2nd CIRP International Seminar on Intelligent Computation in Manufacturing Engineering, pp. 227-232; Wang, J.F., Liu, J.H., Zhong, Y.F., (2005) International Journal Advance Manufacturing Technology, 25, p. 1137; Zhan, Z.H., Zhang, J., (2009) Applications of Evolutionary Computing, pp. 117-122. , Tubingen, Germany; Sanderson, A.C., Homem de Mello, L.S., Zhang, H., (1990) Artificial Intelligence, 11, p. 62; Eberhart, K., (2001), and Shi, Morgan Kaufmann Division of Academic PressChoi, Y.K., Lee, D.M., Cho, Y.B., (2009) Int. J. Adv. Manuf. Technol., 42, p. 180