Optimization of Buffer Allocation in Manufacturing System Using Particle Swarm Optimization
(*) Corresponding author
DOI: https://doi.org/10.15866/iremos.v8i2.5666
Abstract
In this paper, we present heuristic approach to optimize buffer allocation in manufacturing system with tandem, split and merge topologies. Finite Closed queuing network approach is used to represent manufacturing systems. An attempt is made to find near optimal buffer allocation to minimize cost function in unlimited space buffer allocation problem. Expanded Mean Value Analysis is used to evaluate the objective function of closed queuing network. Particle Swarm Optimization is used as generative technique to optimize the buffer allocation. Numerical experiments are shown to explain the effectiveness of procedure.
Copyright © 2015 Praise Worthy Prize - All rights reserved.
Keywords
Full Text:
PDFReferences
I.F.Akyildiz, “On the exact and approximate throughput analysis of closed queuing networks with blocking”. IEEE Transactions on software engineering. 14-1, pp. 62-69, 1988.
http://dx.doi.org/10.1109/32.4623
Chow, W. M., “The cycle time distribution of exponential cycle queues”. Journal of the Association for Computing Machinery, 27(2), pp. 281-286. 1980.
http://dx.doi.org/10.1145/322186.322193
E.A.Gonzales, “Optimal resource allocation in closed finite queuing networks with blocking after service”, Ph.D thesis, Department of Mechanical and Industrial Engineering, University of Massachusetts- Amherst. 1997.
Papadopoulos, H.T., Vidalis, M.I, “Optimal buffer storage allocation in balanced reliable production lines”. International Transactions on Operational Research, 5(4), pp. 325-339. 1998.
http://dx.doi.org/10.1016/s0969-6016(98)00014-8
Spinellis, D.D., Papadopolous, C.T. “A simulated annealing approach for buffer allocation in reliable production lines”. Annals of Operations research, 93, pp. 373-384. 2000.
Spinellis, D.D., Papadopolous, C.T. “Stochastic algorithms for buffer allocation in reliable production lines”. Mathematical Problems in Engineering, 5, pp. 441- 458. 2000.
http://dx.doi.org/10.1155/s1024123x99001180
Spinellis, D., Papadopoulos, C., Smith, J. M. “Large production line optimization using simulated annealing”. International Journal of Production Research, 38(3), pp. 509 – 541. 2000.
http://dx.doi.org/10.1080/002075400189284
Hemachandra. N., Eedupuganti, S.K. “Performance analysis and buffer allocations in some open assembly systems”. Computers, Operations Research, 30, pp. 695 – 704. 2003.
http://dx.doi.org/10.1016/s0305-0548(02)00034-5
S.Daskalaki, J.M.Smith, “Combining routing and buffer allocation problems in serial-parallel queuing networks”. Annals of Operations Research, 125, pp. 47–68, 2004.
http://dx.doi.org/10.1023/b:anor.0000011185.77227.ae
J. M. Smith, F. R. B. Cruz, “The buffer allocation problem for general finite buffer queuing networks”. IIE Transactions,37(4), pp. 343–365, 2005.
http://dx.doi.org/10.1080/07408170590916986
J. M. Smith, F. R. B. Cruz, T. Van Woensel, “Topological networks design of general, finite, multi-server queueing networks”. European Journal of Operational Research, 201(2), pp. 427–441, 2010.
http://dx.doi.org/10.1016/j.ejor.2009.03.012
F. R. B. Cruz, A. R. Duarte, T. Van Woensel, “Buffer Allocation in general single-server queuing networks”. Computers, Operations Research 35(11), pp. 3581-3598. 2008.
http://dx.doi.org/10.1016/j.cor.2007.03.004
M.Yuzukirmizi,J.M. Smith, “Optimal buffer allocation in finite closed networks with multiple servers”. Computers, Operations Research, 35, pp. 2579-2598. 2008
http://dx.doi.org/10.1016/j.cor.2006.12.008
F. R. B. Cruz, T. Van Woensel, J.M. Smith, “Buffer and throughput trade-offs in M/G/1/K queuing networks: A bicriteria approach”. International Journal of Production Economics, 125, pp. 224-234. 2010.
http://dx.doi.org/10.1016/j.ijpe.2010.02.017
F. R. B. Cruz, G.Kendall, L. While, A.R. Duarte, N.L.C. Brito, “Throughput maximization of queueing networks with simultaneous minimization of service rates and buffers”. Mathematical Problems in Engineering. Volume 2012, Article ID 692593.
http://dx.doi.org/10.1155/2012/692593
Can, B., Heavy, C. “A comparison of genetic programming and artificial neural networks in metamodeling of discrete – event simulation models”. Computers, Operations Research. 39(2), pp. 424- 436. 2012.
http://dx.doi.org/10.1016/j.cor.2011.05.004
Demir, L., Tunali, S., Eliiyi, D. T. “The state of art on buffer allocation problem: A comprehensive survey”, Journal of Intelligent Manufacturing, 25(3), pp. 371-392. 2014
http://dx.doi.org/10.1007/s10845-012-0687-9
K.L.Narasimhamu, V.Venugopal Reddy, C.S.P.Rao. “Optimal buffer allocation in tandem closed queuing network with single server using PSO”. Procedia Material Science 5, pp. 2084-2089. 2014.
http://dx.doi.org/10.1016/j.mspro.2014.07.543
Vouros, G. A., Papadopolous, H.T. “Buffer allocation in unreliable production lines using knowledge – based system”. Computers, Operations Research, 25(12), pp. 1005 – 1067. 1998.
http://dx.doi.org/10.1016/s0305-0548(98)00034-3
Gershwin, S. B., Schor, J.E. “Efficient algorithms for buffer space allocation”. Annals of Operations Research, 93, pp. 117- 144. 2000.
http://dx.doi.org/10.1023/a:1018988226612
Seong, D., Chang, Y. S., Hong, Y. “An algorithm for buffer allocation with linear resource constraints in a continuous – flow unreliable production line”. Asia – Pasific Journal of Operational Research, 17, pp. 169-180. 2000.
Papadopoulos, H. T., Vidalis, M. I. “A heuristic algorithm for the buffer allocation in unreliable unbalanced production lines”. Computers, Industrial Engineering, 41, pp. 261-277. 2001.
http://dx.doi.org/10.1016/s0360-8352(01)00051-1
Abdul- Kader, W., Gharbi, A. “Capacity estimation of a multi-product unreliable production line”. International Journal of Production Research, 40(18), pp. 4815-4834. 2002.
http://dx.doi.org/10.1080/0020754021000024148
Tempelmeier, H. “Practical considerations in the optimization of flow production systems”. International Journal of Production Research, 41(1), pp. 149-170. 2003.
http://dx.doi.org/10.1080/00207540210161641
Nourelfath, M., Nahas, N., Ait-Kadi, D. “Optimal design of series production lines with unreliable machines and finite buffers”. Journal of Quality in Maintenance Engineering, 11(2), pp. 121-138. 2005.
http://dx.doi.org/10.1108/13552510510601348
Nahas, N., Ait-Kadi, D., Nourelfath, M. “A new approach for buffer allocation in unreliable production lines”. International Journal of Production Economics, 103, pp. 873-881.
http://dx.doi.org/10.1016/j.ijpe.2006.02.011
Altiparmak, F., Dengiz, B., Bulgak, A. A. “Buffer allocation and performance modeling in asynchronous assembly system operations: An artificial neural network metamodeling approach”. Applied Soft Computing, 7, pp. 946-956. 2007.
http://dx.doi.org/10.1016/j.asoc.2006.06.002
Demir, L., & Tunali, S. “A new approach for optimal buffer allocation in unreliable production lines”. Pcoceedings of 38th International Conference on Computers , Industrial Engineering, pp. 1962-1970. 2008.
Lee. H.T., Chen, S.K., Shunder Chang, S. A meta-heuristic approach to buffer allocation in production line. Journal of C.C.I.T. 38(1), pp 167- 178. 2009.
Demir, L., Tunali, S., Eliiyi, D. T. “An adaptive tabu search approach for buffer allocation problem in unreliable production lines”. 24th Mini EURO conference on continuous optimization and information based technologies in the financial sector, selected papers, pp. 207-212.2010.
Demir, L., Tunali, S., Lokketangen, A. “A tabu search approach for buffer allocation in production lines with unreliable machines”. Engineering Optimization, 43(2) pp. 213-231. 2011.
http://dx.doi.org/10.1080/0305215x.2010.481022
Demir, L., Tunali, S., Eliiyi, D. T. “An adaptive tabu search approach for buffer allocation problem in unreliable non-homogenous production lines”. Computers, Operations Research, 39(7), pp. 1477-1486. 2012.
http://dx.doi.org/10.1016/j.cor.2011.08.019
Chehade, H., Yalaoui, F., Amodeo, L., Dugardin, F. “Buffers sizing in assembly lines using Lorenz multiobjective ant colony optimization algorithm”. IEEE International Conference on Machine and Web Intelligence, pp. 283-287. 2010.
http://dx.doi.org/10.1109/icmwi.2010.5647916
Kose, S. Y., Demir. L., Tunali, S., Eliiyi, D. T. “Capacity improvement using simulation optimization approaches: A case study in the thermos technology industry”. Engineering Optimization, 47(2), pp. 149-164. 2015.
http://dx.doi.org/10.1080/0305215x.2013.875166
Ramya, S., Rajesh, N.B., Viswanathan, B., Karthika Vigneswari, B., Particle swarm optimization (PSO) based optimum distributed generation (DG) location and sizing for voltage stability and loadability enhancement in radial distribution system, (2014) International Review of Automatic Control (IREACO), 7 (3), pp. 288-293.
Ananth, G., Vinayagam, B.K., A study on the PSO model based fast track total productive maintenance for small and tiny enterprises, (2014) International Review of Mechanical Engineering (IREME), 8 (5), pp. 941-947.
http://dx.doi.org/10.15866/ireme.v8i5.3533
Refbacks
- There are currently no refbacks.
Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize