A comparative study of production control mechanisms using simulation-based multi-objective optimisation

References

• Andijani , AA and Anwarul , M . 1997 . Manufacturing blocking discipline: A multi-criterion approach for buffer allocations . International Journal of Production Economics , 51 : 155 – 163 .
   Web of Science ®Google Scholar
• April, J., Better, M., Glover, F. and Kelly, J., 2004. New advances and applications for marrying simulation and optimisation. In: R.G. Ingalls, M.D. Rossetti, J.S. Smith and B.A. Peters, eds. Proceedings of winter simulation conference, 5–8 December, Washington, DC, USA. IEEE Computer Society, 80–86
   Google Scholar
• Altiparmak, F., Dengiz, B. and Bulgak, A.A., 2002. Optimisation of buffer sizes in assembly systems using intelligent techniques. In: E. Yücesan, C.-H. Chen, J.L. Snowdon and J.M. Charnes, eds. Proceedings of winter simulation conference, 8–11 December, Piscataway, New Jersey, USA. San Diego, California: IEEE, 1157–1162
   Google Scholar
• Altiparmak , F , Dengiz , B and Bulgak , AA . 2007 . Buffer allocation and performance modeling in asynchronous assembly system operations: an artificial neural network metamodeling approach . Applied Soft Computing , 7 ( 3 ) : 946 – 956 .
   Web of Science ®Google Scholar
• Babbar, M., Lakshmikantha, A. and Goldberg, D.E., 2003. A modified NSGA-II to solve noisy multiobjective problems. Proceedings of genetic and evolutionary computation conference (GECCO), 12–16 July, Chicago, Illinois, USA. AAAI, 21–27
   Google Scholar
• Blackstone , J.H. Jr and Cox , J.F.C. III . 2002 . Designing unbalanced lines – understanding protective capacity and protective inventory . Production Planning & Control , 13 ( 4 ) : 416 – 423 .
   Web of Science ®Google Scholar
• Bonvik , AM , Couch , CE and Gershwin , SB . 1997 . A comparison of production-line control mechanisms . International Journal of Production Research , 35 ( 3 ) : 789 – 804 .
   Web of Science ®Google Scholar
• Bulgak , AA , Diwan , PD and Inozu , B . 1995 . Buffer size optimisation in asynchronous assembly systems using genetic algorithms . Computers and Industrial Engineering , 28 ( 2 ) : 309 – 322 .
   Web of Science ®Google Scholar
• Buzacott , JA and Shanthikumar , JG . 1993 . Stochastic models of manufacturing systems , Englewood Cliffs, New Jersey : Prentice Hall .
   Google Scholar
• Can, B., Beham, A. and Heavey, C., 2008. A comparative study of genetic algorithm components in simulation–based optimisation. In: S.J. Mason, R.R. Hill, L. Mönch, O. Rose, T. Jefferson and J.W. Fowler, eds. Proceedings of winter simulation conference, 7–10 December, Miami, Florida, USA. Piscataway, New Jersey: IEEE Press, 1829–1837
   Google Scholar
• Chan , FTS and Ng , EYH . 2002 . Comparative evaluations of buffer allocation strategies in a serial line . International Journal of Advanced Manufacturing Technology , 19 : 789 – 800 .
   Web of Science ®Google Scholar
• Coello Coello , CA , Lamont , GB and Veldhuisen , DAV . 2007 . Evolutionary algorithms for solving multi-objective problems , 2nd edn , New York : Springer .
   Google Scholar
• Conway , R , Maxwell , W , Mcclain , JO and Thomas , LJ . 1988 . The role of work-in-process inventory in serial production lines . Operations Research , 36 : 229 – 241 .
   Web of Science ®Google Scholar
• Deb , K . 2001 . Multi-objective optimisation using evolutionary algorithms , 3rd edn , Chichester , , UK : Wiley .
   Google Scholar
• Deb , K , Pratap , A , Agarwal , S and Meyarivan , T . 2002 . A fast and elitist multi-objective genetic algorithm: NSGA-II . IEEE Transaction on Evolutionary Computation , 6 ( 2 ) : 181 – 197 .
   Web of Science ®Google Scholar
• Ding , H , Benyoucef , L and Xie , X . 2008 . Stochastic multi-objective production-distribution network design using simulation-based optimisation . International Journal of Production Research , 47 ( 2 ) : 479 – 505 .
   Web of Science ®Google Scholar
• Dudley , NA . 1963 . Work time distributions . International Journal of Production Research , 2 ( 2 ) : 137 – 144 .
   Google Scholar
• Enns, S.T., 2007. ‘Pull’ replenishment performance as a function of demand rates and setup times under optimal settings. In: S.G. Henderson, B. Biller, M.-H. Hsieh, J. Shortle, J.D. Tew and R.R. Barton, eds. Proceedings of winter simulation conference, 9–12 December, Miami, Florida, USA. IEEE Press, 1624–1632
   Google Scholar
• Enns, S.T. and Rogers, P., 2008. Clarifying CONWIP versus push system behavior using simulation. In: S.J. Mason, R.R. Hill, L. Mönch, O. Rose, T. Jefferson and J.W. Fowler, eds. Proceedings of winter simulation conference, 7–10 December, Miami, Florida, USA. Piscataway, New Jersey: IEEE Press, 1867–1872
   Google Scholar
• Framinan , JM , González , PL and Ruiz-Usano , R . 2003 . The CONWIP production control system: review and research issues . Production Planning & Control , 14 ( 3 ) : 255 – 265 .
   Web of Science ®Google Scholar
• Gaury , EGA , Pierreval , H and Kleijnen , JPC . 2000 . An evolutionary approach to select a pull system among Kanban, CONWIP and hybrid . Journal of Intelligent Manufacturing , 11 : 157 – 167 .
   Web of Science ®Google Scholar
• Geraghty , J and Heavey , C . 2004 . A comparison of hybrid push/pull and CONWIP/pull production inventory control policies . International Journal of Production Economics , 91 : 75 – 90 .
   Web of Science ®Google Scholar
• Gershwin , SB . 1987 . An efficient decomposition method for the approximate evaluation of tandem queues with finite storage space and blocking . Operation Research , 35 ( 2 ) : 291 – 305 .
   Web of Science ®Google Scholar
• Graves , RJ , Konopka , JM and Milne , RJ . 1995 . Literature review of material flow control mechanisms . Production Planning & Control , 6 ( 5 ) : 395 – 403 .
   Web of Science ®Google Scholar
• Hillier , FS and So , KC . 1991 . The effect of the coefficient of variation of operation times on the allocation of storage space in production line systems . IIE Transactions , 23 : 198 – 206 .
   Web of Science ®Google Scholar
• Hodgson , TJ and Wang , D . 1991 . Optimal hybrid push/pull control strategies for a parallel multi-stage system: Part I . International Journal of Production Research , 29 ( 6 ) : 1279 – 1287 .
   Web of Science ®Google Scholar
• Hopp , WJ and Spearman , ML . 2000 . Factory physics: foundations of manufacturing management , 2nd edn , Burr Ridge , IL : Irwin McGraw-Hill Higher Education .
   Google Scholar
• Kim , S , Davis , KR and Cox , JF . 2003 . An investigation of output flow control, bottleneck flow control and dynamic flow control mechanisms in various simple lines scenarios . Production Planning & Control , 14 ( 1 ) : 15 – 32 .
   Web of Science ®Google Scholar
• Koh , S-G and Bulfin , RL . 2004 . Comparison of DBR with CONWIP in an unbalanced production line with three stations . International Journal of Production Research , 42 ( 2 ) : 391 – 404 .
   Web of Science ®Google Scholar
• Knowles, J. and Corne, D., 2002. On metrics for comparing non-dominated sets. Congress on evolutionary computation (CEC 2002), 12–17 May, Honolulu, Hawaii, USA. Washington, DC: IEEE Computer Society, 711–716
   Google Scholar
• Knowles, J., 2005. A summary-attainment-surface plotting method for visualising the performance of stochastic multiobjective optimisers. Proceedings of the 5th international conference on intelligent systems design and applications (ISDA), 8–10 September, Wroclaw, Poland. IEEE Computer Society, 552–557
   Google Scholar
• Lacksonen , T . 2001 . Empirical comparison of search algorithms for discrete event simulation . Computers and Industrial Engineering , 40 ( 1–2 ) : 133 – 148 .
   Web of Science ®Google Scholar
• Laguna , M and Martí , R . 2002 . “ The OptQuest callable library ” . In Optimisation software class libraries , Edited by: Voß , S. and Woodruff , D. 193 – 218 . Boston : Kluwer Academic Publishers .
   Google Scholar
• Laguna , M and Martí , R . 2003 . Scatter search: Methodology and implementations in C , Boston : Kluwer Academic Publishers .
   Google Scholar
• Law , AM and Kelton , WD . 2000 . Simulation modeling and analysis , 3rd edn , Burr Ridge , IL : McGraw-Hill Higher Education .
   Google Scholar
• Little , JDC . 1992 . “ Are there ‘laws’ of manufacturing, manufacturing systems? ” . In Foundations of world-class practice , Edited by: Heim , J.A. and Compton , W.D. 180 – 188 . Washington , DC : National Academy Press .
   Google Scholar
• Lutz , CM , Davis , KR and Sun , M . 1998 . Determining buffer location and size in production line using Tabu search . European Journal of Operation Research , 106 : 301 – 316 .
   Web of Science ®Google Scholar
• MacDonald, C. and Gunn, E., 2008. A simulation based system for analysis and design of production control systems. In: S.J. Mason, R.R. Hill, L. Mönch, O. Rose, T. Jefferson and J.W. Fowler, eds. Proceedings of winter simulation conference, 7–10 December, Miami, Florida, USA. Piscataway, New Jersey: IEEE Press, 1882–1890
   Google Scholar
• Mathews , P . 2005 . Design of experiments with Minitab , Milwaukee, Wisconsin : American Society of Quality .
   Google Scholar
• Ng, A., Urenda, M., Svensson, J., Skoogh, A. and Johansson, B., 2007. FACTS Analyzer: An innovative tool for factory conceptual design using simulation. Proceedings of Swedish production symposium 2007 (SPS’07), 28–30 August, Gothenburg
   Google Scholar
• Ng, A., Syberfeldt, A., Grimm, H. and Svensson, J., 2008. Multi-objective simulation optimisation and significant dominance for comparing production control mechanisms. 18th international conference on flexible automation and intelligent manufacturing (FAIM’08), 30 June–2 July, Skövde, Sweden: University of Skövde, 1210–1219
   Google Scholar
• So , KC . 1997 . Optimal buffer allocation strategy for minimising work-in-process inventory in unpaced production lines . IIE Transactions , 29 : 81 – 88 .
   Web of Science ®Google Scholar
• Spearman , ML , Woodruff , DL and Hopp , WJ . 1990 . CONWIP: A pull alternative to Kanban . International Journal of Production Research , 28 ( 5 ) : 879 – 894 .
   Web of Science ®Google Scholar
• Spinellis , DD and Papadopoulos , CT . 2000a . A simulated annealing approach for buffer allocation in reliable production lines . Annals of Operations Research , 93 : 373 – 384 .
   Web of Science ®Google Scholar
• Spinellis , DD and Papadopoulos , CT . 2000b . Stochastic algorithms for buffer allocation in reliable production lines . Mathematical Problems in Engineering , 5 : 441 – 458 .
   Web of Science ®Google Scholar
• Takahashi , K , Morikawa , K and Chen , Y-C . 2007 . Comparing Kanban control with the theory of constraints using Markov chains . International Journal of Production Research , 45 ( 16 ) : 3599 – 3617 .
   Web of Science ®Google Scholar
• Zitzler , E and Thiele , L . 1998 . “ Multiobjective optimisation using evolutionary algorithms – a comparative case study ” . In Conference: the 5th international conference on parallel problem solving from nature (PPSN V), 27–30 September, Amsterdam, The Netherlands , Edited by: Eiben , A.E. , Bäck , T. , Schoenauer , M. and Schwefel , H.-P. 292 – 301 . Berlin , , Germany : Springer .
   Google Scholar
• Zitzler, E., Laumanns, M., Thiele, L., Fonseca, C.M. and Fonseca, V.G.D., 2002. Why quality assessment of multiobjective optimisers is difficult. Proceedings of the genetic and evolutionary computation conference, 9–13 July, New York. Morgan Kaufmann Publishers Inc., 666–674
   Google Scholar