Buradasınız

Developing a Mathematical Model Based on Multiple Traveling Salesman Problem for Determining Machine Groups in a Cell Formation Problem

Journal Name:

Publication Year:

Abstract (2. Language): 
Cellular manufacturing system is one of the modern manufacturing methods which has been recently utilized with industries because of its advantages. Cellular manufacturing is one of the applications of group technology in manufacturing systems which deals with the determining of machine cells and part families. The determining process is called cell formation problem. In this paper, the cell formation problem is formulated as a multiple travelling salesman problem with applying the dissimilarity coefficient defined as the cost of traveling between two nodes. To verify the performance of the proposed method, a number of test problems selected from the literature are solved and the obtained solutions are compared with those of previous well-known methods using the grouping efficacy measure.
185-190

REFERENCES

References: 

[1] Mitrofanov, S. P., (1966). The scientific principles of group technology. Boston Spa, Yorks, UK: National Lending Library Translation.
[2] Heragu, S. S., (1994). Group technology and cellular manufacturing. IEEE Transactions on Systems, Man and Cybernetics, 24(2), 203-214.
[3] Wemmerlov, U., Hyer, N. L., (1989). Cellular manufacturing in the US industry: a survey of users. International Journal of Production Research, 27(9), 1511-1530.
[4] Wemmerlov, U., Hyer, N., (1987). Research issues in cellular manufacturing. International Journal of Production Research, 25, 413-31.
[5] Selim, H. M., Askin, R. G. and Vakharia, A.J., (1998). Cell Formation in group technology: review, evaluation and direction for future research. Computers & Industrial Engineering, 34(3), 3-20.
[6] Mansouri, S. A., Moattar-Hussein, S. M. and Newman, S. T., (2000). A review of the modern approaches to multi-criteria cell design. International Journal of Production Research, 38(5), 1201-1218.
[7] Jabalameli, M. S., Arkat, J., Shoresh Sakri, M., (2008), Applying metaheuristics in the generalized cell formation problem considering machine reliability, Journal of the Chinese Institute of Industrial Engineers, 25(4), 261-274.
[8] Yin, Y., Yasuda, K., (2006). Similarity coefficient methods applied to the cell formation problem: A taxonomy and review. International Journal of Production Economics, 101, 329-352.
[9] Chen, S. J., Cheng, C. S., (1995). A neural network based cell formation algorithm in cellular manufacturing. International Journal of Production Research, 33(2), 293- 318.
[10] Mahdavi, I., Kaushal, O. P., Chandra, M., (2001). Graph-neural network approach in cellular manufacturing on the basis of a binary system. International Journal of Production Research, 39 (13), 2913-2922.
[11] Onwubolu, G. C., Mutingi, M., (2001), A genetic algorithm approach to cellular manufacturing systems. Computers & Industrial Engineering, 39, 125-144.
[12] Soleymanpour, M., Vrat, P., Shanker, R., (2002). A transiently chaotic neural network approach to the design of
cellular manufacturing. International Journal of Production Research, 40(10), 2225-2244.
[13] Chen, M. M., Wu, C.M., Chen, C. L. (2002), An integrated approach of ART1 and tabu search to solve cell formation problems, Journal of the Chinese Institute of Industrial Engineers,19(3), 62-74.
[14] Goncalves, J., Resende, M., (2004) An evolutionary algorithm for manufacturing cell formation. Computers & Industrial Engineering, 47, 247-73.
[15] Albadawi, Z., Bashir, H. A., Chen, M., (2005). A mathematical approach for the formation of manufacturing cells. Computers & Industrial Engineering, 48, 3-21.
[16] Mahdavi, I., Javadi, B., F. Alipour, K., Slomp, J., (2007). Designing a new mathematical model for cellular manufacturing system based on cell utilization. Applied Mathematics and Computation, 190, 662–670.
[17] Yang, M. S., Yang, J. H. (2008). Machine–part cell formation in group technology using a modified ART1 method. European Journal of Operational Research, 188, 140-152.
[18] Mahdavi, I., Paydar, M. M., Solimanpur, M., Heidarzade, A., (2009). Genetic algorithm approach for solving a cell formation problem in cellular manufacturing. Expert Systems with Applications, 36, 6598- 6604.
[19] Díaz, J. A., Luna, D., Luna, R., (2010). A GRASP heuristic for the manufacturing cell formation problem. Top, DOI: 10.1007/s11750-010-0159-3.
[20] Anvari, M., Saidi Mehrabad, M., Barzinpour, F., (2010). Machine–part cell formation using a hybrid particle swarm optimization. International Journal of Advanced Manufacturing Technology, 47, 745-754.
[21] Paydar, M. M., Mahdavi, I., Valipoor Khonakdari, S., Solimanpur, M. (2011). Developing a mathematical model for cell formation in cellular manufacturing systems. International Journal of Operational Research, 11(4), 408-424.
[22] Arkat, A., Hosseini, L., Hosseinabadi Farahani, M., (2011). Minimization of exceptional elements and voids in the cell formation problem using a multi-objective genetic algorithm. Expert Systems with Applications, 38, 9597-9602.
[23] Kara, I., Bektas, T., (2006). Integer linear programming formulations of multiple salesman problems and its variations. European Journal of Operational Research, 174, 1449-1458.
[24] King, R. E., Nakornchai, V., (1982). Machine-component group formation in group technology: Review and extension. International Journal of Production Research, 20(2), 117-133.
[25] Waghodekar, P. H., Sahu, S., (1984). Machine-component cell formation in group technology MACE. International Journal of Production Research, 22, 937- 948.
[26] Seifoddini, H., (1989). A note on the similarity coefficient method and the problem of improper machine assignment in group technology applications. International Journal of Production Research, 1989, 27(7), 1161-1165.
[27] Kusiak, A., Cho, M., (1992). Similarity coefficient algorithm for solving the group technology problem. International Journal of Production Research, 30(11), 2633-2646.
[28] Boctor, F. F., (1991). A linear formulation of the machine-part cell formation problem. International Journal of Production Research, 29(2), 343-56.
[29] Seifoddini, H., (1989). A note on the similarity coefficient method and the problem of improper machine assignment in group technology applications. International Journal of Production Research, 27(7), 1161-1165.
Journal of Control Engineering and Technology (JCET)
JCET Vol. 2 Iss. 4 October 2012 PP. 185-190 www.ijcet.org ○C World Academic Publishing
190
[30] Chandrasekharan, M. P. and Rajagopalan, R., (1986). An ideal seed nonhierarchical clustering algorithm for cellular manufacturing. International Journal of Production Research, 24, 451- 464.
[31] Mosier, C. T., Taube, L., (1985). The facets of group technology and their impact on implementation. OMEGA, 13(5), 381-391.
[32] Chan, H. M., Milner, D. A., (1982). Direct clustering algorithm for group formation in cellular manufacture. Journal of Manufacturing Systems, 1, 65-75.
[33] Zolfaghari, S., Liang, M., (1997), An objective-guided ortho-synapse Hopfield network approach to machine grouping problems. International Journal of Production Research, 35(10), 2773-2792.
[34] Chandrasekharan, M. P., Rajagopalan, R., (1986). MODROC: an extension of rank order clustering for group technology. International Journal of Production Research, 24(5), 1221-1264.
[35] Kumar, C., Chandrasekharan, M., (1990). Grouping efficacy: a quantitative criterion for goodness of block diagonal forms of binary matrices in group technology. International Journal of Production Research, 28, 233-243.
[36] Chandrasekharan, M. P., Rajagopalan, R., (1987). ZODIAC - an algorithm for concurrent formation of part-families and machine-cells. International Journal of Production Research, 25, 835- 850.
[37] Srinivasan, G., Narendran, T. T., (1991). GRAFICS - a non hierarchical clustering algorithm for group technology. International Journal of Production Research, 29, 463- 478.
[38] Cheng, C., Gupta, Y., Lee, W., Wong, K., (1998). A TSP-based heuristic for forming machine groups and part families. International Journal of Production Research, 36, 1325-37.
[39] Tariq, A., Hussain, I., Ghafoor, A. (2009). A hybrid genetic algorithm for machine-part grouping. Computers & Industrial Engineering, 56, 347-356.

Thank you for copying data from http://www.arastirmax.com