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Models for the optimal design of flexible manufacturing systems

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Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

Abstract

In this chapter models applicable during the basic planning stage for the optimal design of flexible manufacturing systems are studied. An overview of the models already existing in literature is presented together with new models developed by the author.

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Literature

  1. Secco-Suardo, G.: Optimization of closed queueing networks, in: Complex Materials Handling and Assembly Systems Final Report Vol. III No. ESL-FR-834–3, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, pp.31–32;

    Google Scholar 

  2. Secco-Suardo, G.: Workload Optimization in a FMS Modelled as a Closed Network of Queues, in: Annals of the CIRP, 28(1979)1, p.382

    Google Scholar 

  3. Kimemia, J.G., Gershwin, S.B.: Multicommodity Network Flow Optimization in Flexible Manufacturing Systems, in: Complex Materials Handling and Assembly Systems Final Report Vol. II No. ESL-FR-834–2, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, pp.35–37;

    Google Scholar 

  4. Kimemia, J.G., Gershwin, S.B.: Network Flow Optimization in Flexible Manufacturing Systems, in: Proc. IEEE Conf. on Decision and Control 1979 pp.633–639;

    Google Scholar 

  5. Kimemia, J.G., Gershwin, S.B.: Flow Optimization in Flexible Manufacturing Systems, in: IJPR 23(1985)1, pp.81–96

    Google Scholar 

  6. Avonts, L.H., Gelders, L.F., Wassenhove Van, L.N.: Allocation work between an FMS and a conventional jobshop: A case study, in: EJOR, 33(1988), pp.245–256

    Google Scholar 

  7. see chapter 4.2.2

    Google Scholar 

  8. The model presented is an essence out of two publications on the model: Kimemia, J.G., Gershwin, S.B.: Multicommodity Network Flow Optimization in Flexible Manufacturing Systems, in: Complex Materials Handline and Assembly Systems Final Report Vol. II No. ESL-FR-834–2, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, pp.31–32;

    Google Scholar 

  9. Kimemia, J.G., Gershwin, S.B.: Network Flow Optimization in Flexible Manufacturing Systems, in: Proc. IEEE Conf. on Decision and Control 1979 pp.634–635; Note that in the second paper the fixation of the production rate by constraint sets (2.2) and (2.4) has to be eliminated if our aim is to maximize total production in the objective function (2.10). It is only necessary to fix the relative amounts of production between different parts (see constraint (2.31) or (2.28) in the first paper). Further the continuity of operational flow must be ensured and is missing in the second paper (see constraint set (2.27) in the first paper).

    Google Scholar 

  10. Kimemia, J.G., Gershwin, S.B.: Multicommodity Network Flow Optimization in Flexible Manufacturing Systems, in: Complex Materials Handling and Assembly Systems Final Report Vol. II No. ESL-FR-834–2, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, p.25

    Google Scholar 

  11. Secco-Suardo, G.: Optimization of closed queueing networks, in: Complex Materials Handling and Assembly Systems Final Report Vol. III No. ESL-FR-834–3, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, pp.21–22;

    Google Scholar 

  12. Gerla, M.: The design of store-and-forward (S/F) networks for computer communications, Ph.D. thesis Dep. Comp. Science, Univ. Calif. Los Angeles, 1973;

    Google Scholar 

  13. Cantor, D.G., Gerla, M.: Optimal Routing in a Packet Switched Computer Network, in: IEEE Trans, on Computers, C-23(1974)10, pp.1062–1069;

    Google Scholar 

  14. Kimemia, J.G., Gershwin, S.B.: Multicommodity Network Flow Optimization in Flexible Manufacturing Systems, in: Complex Materials Handling and Assembly Systems Final Report Vol. II No. ESL-FR-834–2, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, pp.47,

    Google Scholar 

  15. Kimemia, J.G., Gershwin, S.B.: Multicommodity Network Flow Optimization in Flexible Manufacturing Systems, in: Complex Materials Handling and Assembly Systems Final Report Vol. II No. ESL-FR-834–2, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, pp. 51–63;

    Google Scholar 

  16. Kimemia, J.G., Gershwin, S.B.: Network Flow Optimization in Flexible Manufacturing Systems, in: Proc. IEEE Conf. on Decision and Control 1979 pp.635–636;

    Google Scholar 

  17. Kimemia, J.G., Gershwin, S.B.: Multicommodity Network Flow Optimization in Flexible Manufacturing Systems, in: Complex Materials Handling and Assembly Systems Final Report Vol. II No. ESL-FR-834–2, Electr. Syst. Lab. M.I.T., Cambridge MA, July 1978, p.25

    Google Scholar 

  18. Yao, D.D., Shanthikumar, J.G.: The optimal input rates to a system of manufacturing cells, in: INFOR, 25(1987)1, pp.57–65

    Google Scholar 

  19. Yao, D.D., Shanthikumar, J.G.: Some resource allocation problems in multi-cell systems, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, edited by ICE. Stecke and R. Suri, Amsterdam 1986, pp.250–253

    Google Scholar 

  20. Yao, D.D., Shanthikumar, J.G.: Some resource allocation problems in multi-cell systems, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, edited by K.IE. Stecke and R. Suri, Amsterdam 1986, p.250

    Google Scholar 

  21. for the proof of convexity of the model and a proof for convergence of the algorithm to the optimal solution see: Yao, D.D., Shanthikumar, J.G.: The optimal input rates to a system of manufacturing cells, in: INFOR, 25(1987)1, pp.57–65;

    Google Scholar 

  22. Kobayashi, H., Gerla, M.: Optimal Routing in Closed Queueing Networks, in: ACM Trans. Comp. Syst., 1(1983)4, pp.294–310; For a description of the FD-Algorithms, see chapter 6.1.1.2.

    Google Scholar 

  23. Little, J.D.C.: A Proof of the Queueing Formula L = λ • W, in: OR 9(1961), pp.383–387

    Google Scholar 

  24. See definitions of workloads in chapter 6.1.2.2.2

    Google Scholar 

  25. Stecke, K.E.: On the Nonconcavity of Throughput in Certain Closed Queueing Networks, in: Performance Evaluation, 6(1986), pp.293–305

    Google Scholar 

  26. Gordon, K.D., Dowdy, L.W.: The Impact of Certain Parameter Estimation Errors in Queueing Network Models, in: ACM Perf. Eval. Rev., 2(May 1980) pp.3–9

    Google Scholar 

  27. see chapter 6.1.2.2.2 for the different definitions of relative workloads

    Google Scholar 

  28. Further results of concavity and convexity in Closed Queueing Networks theory are shown in chapter 6.1.2.2.3

    Google Scholar 

  29. Fiacco, A.V., McCormick, G.B.: Nonlinear Programming: Sequential Unconstrained Minimization Techniques, New York 1968, pp.19–20

    Google Scholar 

  30. Kobayashi, H., Gerla, M.: Optimal Routing in Closed Queueing Networks, in: ACM Trans. Comp. Syst., 1(1983)4, p.303

    Google Scholar 

  31. Kobayashi, H., Gerla, M.: Optimal Routing in Closed Queueing Networks, in: ACM Trans. Comp. Syst., 1(1983)4, p.303

    Google Scholar 

  32. Shalev-Oren, S., Seidmann, A., Schweitzer, P J.: Analysis of Flexible Manufacturing Systems with Priority Scheduling: PMVA, in: Annals of Operation Research, 3(1985), pp.115–139

    Google Scholar 

  33. see chapter 4.2.2

    Google Scholar 

  34. see chapter 6.1.2.2

    Google Scholar 

  35. see Appendix A

    Google Scholar 

  36. Buzen, J.P.: Computational Algorithms for Closed Queueing Networks with Exponential Servers, in: Comm. ACM, 16(1973)9, p.530

    Google Scholar 

  37. see chapter 4.2.2 and 15

    Google Scholar 

  38. for a description of this solution procedure refer to chapter 6.1.1.1

    Google Scholar 

  39. Stecke, K.E.: On the Nonconcavity of Throughput in Certain Closed Queueing Networks, in: Performance Evaluation, 6(1986), pp.296–297

    Google Scholar 

  40. see chapter 6.1.1.1

    Google Scholar 

  41. Bazaraa, M.S., Shetty, C.M.: Nonlinear Programming: Theory and Algorithms, New York 1979, p.148

    Google Scholar 

  42. see Stecke, K.E., Solbcre, J.J.: The Optimal Planning of Computerized Manufacturing Systems, School of Industrial Engineering, Perdue University, Report No.20, West Lafayette, Indiana 1981, p. 125

    Google Scholar 

  43. see chapter 6.1.2.2

    Google Scholar 

  44. Vinod, B., Solberg, J.J.: The optimal design of flexible manufacturing systems, in: IJPR, 23(1985)23, pp.1141–1151

    Google Scholar 

  45. see chapter 6.1.1.2

    Google Scholar 

  46. Vinod, B., Solberg, J.J.: The optimal design of flexible manufacturing systems, in: LJPR, 23(1985)23, pp. 1146–1150

    Google Scholar 

  47. Dallery, Y., Frein, Y.: An efficient Method to determine the optimal Configuration of a Flexible Manufacturing System, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, Ed.: K.E. Stecke and R. Suri, Amsterdam 1986, pp.272–275

    Google Scholar 

  48. A proof is given in Shanthikumar, J.G., Yao, D.D.: Optimal Server Allocation in a System of Multi-Server Stations, in: MS, 33(1987)9, pp.1173–1180

    Google Scholar 

  49. A proof is given in Suri, R.: A Concept of Monotonicity and Its Characterization for Closed Queueing Networks, in: OR, 33(1985)3, pp.606–624

    Google Scholar 

  50. Vinod, B., Solberg, J.J.: The optimal design of flexible manufacturing systems, in: LIPR, 23(1985)23, p. 1144

    Google Scholar 

  51. Vinod, B., Solberg, J.J.: The optimal design of flexible manufacturing systems, in: IJPR, 23(1985)23, p.1147

    Google Scholar 

  52. Dallery, Y., Frein, Y.: An efficient Method to determine the optimal Configuration of a Flexible Manufacturing System, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, Ed.: ICE. Stecke and R. Suri, Amsterdam 1986, p.2/0

    Google Scholar 

  53. Denning, P.J., Buzcn, J.P.: The operational analysis of qucueing network models, in: Computing Surveys, 10(1978)3, pp.225–262

    Google Scholar 

  54. Kleinrock, L. Queueing Systems, Vol.2 New York 1976 pp.219–225

    Google Scholar 

  55. see chapter 6.1.2.2

    Google Scholar 

  56. Dallery, Y., Frein, Y.: An Efficient Method to determine the Optimal Configuration of a Flexible Manufacturing System, in: Annals or OR, 15(1988), pp.207–225

    Google Scholar 

  57. for a description of mean value analysis see chapter 6.1.2.3.

    Google Scholar 

  58. Denning, P.J., Buzen, J.P.: The operational analysis of queueing network models, in: Computing Surveys, 10(1978)3, p.225

    Google Scholar 

  59. see chapter 6.1.2.2

    Google Scholar 

  60. Shanthikumar, J.G., Yao, D.D.: On server allocation in multiple center manufacturing systems, in: OR, 36(1988)2, pp.333–342;

    Google Scholar 

  61. Yao, D.D., Shanthikumar, J.G.: Some resource allocation problems in multi-cell systems, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, edited by K.E. Stecke and R. Suri, Amsterdam 1986, pp.249–250

    Google Scholar 

  62. A proof can be found in Shanthikumar, J.G., Yao, D.D.: On server allocation in multiple center manufacturing systems, in: OR, 36(1988)2, pp.335–336

    Google Scholar 

  63. Eager, D.L., Sevcik, K.C.: Performance Bound Hierarchies for Queueing Networks, in: ACM Trans. Comp. Syst., 1(1983), pp.99–115

    Google Scholar 

  64. Shanthikumar, J.G., Yao, D.D.: On server allocation in multiple center manufacturing systems, in: OR, 36(1988)2, p.338;

    Google Scholar 

  65. Fox, B.: Discrete Optimization via Marginal Analysis, in: MS, 13(1966), pp.210–216

    Google Scholar 

  66. see chapter 6.1.2.2

    Google Scholar 

  67. Shanthikumar, J.G., Yao, D.D.: Optimal server allocation in a system of multi-server stations, in: MS, 33(1987)9, p.1174

    Google Scholar 

  68. Fox, B.: Discrete Optimization via Marginal Analysis, in: MS, 13(1966), pp.210–216

    Google Scholar 

  69. Shanthikumar, J.G., Yao, D.D.: Optimal server allocation in a system of multi-server stations, in: MS, 33(1987)9, p.1176

    Google Scholar 

  70. see definitions in chapter 2.1

    Google Scholar 

  71. Yao, D.D., Shanthikumar, J.G.: Some resource allocation problems in multi-cell systems, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, edited by K.E. Stecke and R. Suri, Amsterdam 1986, pp.245–249;

    Google Scholar 

  72. Shanthikumar, J.G., Yao, D.D.: Optimal Buffer Allocation in a Multiceli System, in: The International Journal of Flexible Manufacturing Systems, 1(1989), pp.347–356

    Google Scholar 

  73. see chapter 6.1.2.2 and Gordon, W.J., Newell, G.F.: Closed Queueing Networks with Exponential Servers, in: OR, 15(1967), pp.252–267

    Google Scholar 

  74. Jackson, J.R.: Jobshop-Likc Queueing Systems, in: MS, 10(1963), pp.131–142

    Google Scholar 

  75. Fox, B.: Discrete Optimization via Marginal Analysis, in: MS, 13(1966), pp.210–216

    Google Scholar 

  76. Yao, D.D., Shanthikumar, J.G.: Some resource allocation problems in multi-cell systems, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, edited by K.E. Stecke and R. Suri, Amsterdam 1986, p.248

    Google Scholar 

  77. Note that in the original model formulation by Shanthikumar and Yao constraint (8.2.5.2) is an equality. Above the constraint has been changed to an inequality. This is because it is possible that all cells have been eliminated before the actual number of buffers reaches N.

    Google Scholar 

  78. Yao, D.D., Shanthikumar, J.G.: Some resource allocation problems in multi-cell systems, in: Proc. 2nd ORSA/TIMS Conf. on Flexible Manufacturing Systems: Operations Research Models and Applications, edited by ICE. Stecke and R. Suri, Amsterdam 1986, p.247

    Google Scholar 

  79. Jackson, J.R.: Jobshop-Like Queueing Systems, in: MS, 10(1963), pp.131–142;

    Google Scholar 

  80. Gordon, W.J., Newell, G.F.: Closed Queueing Networks with Exponential Servers, in: OR, 15(1967), pp.252–267

    Google Scholar 

  81. Solot, P.: Optimizing a Flexible Manufacturing System with several Pallet Types, Working Paper O.R.W.P. 87/17, Ecole Polytechnique Fédéral de Lausanne, Département de Mathématiques, Lausanne Sept. 1987, p.7

    Google Scholar 

  82. Solot, P.: Optimizing a Flexible Manufacturing System with several Pallet Types, Working Paper O.R.W.P. 87/17, Ecole Polytechnique Fédéral de Lausanne, Département de Mathématiques, Lausanne Sept. 1987, p.7

    Google Scholar 

  83. Solot, P.: Optimizing a Flexible Manufacturing System with several Pallet Types, Working Paper O.R.W.P. 87/17, Ecole Polytechnique Fédéral de Lausanne, Département de Mathématiques, Lausanne Sept. 1987, p.10

    Google Scholar 

  84. a description of the program MULTIQ can be found in: Solot, P., Bastos, J.M.: Choosing a Queueing Model for FMS, Working Paper O.R.W.P. 87/05, Ecole Polytechnique Fédéral de Lausanne, Département de Mathématiques, Lausanne 1987

    Google Scholar 

  85. see chapter 6.1.2.2

    Google Scholar 

  86. Zahorjan, J., Sevcik, K.C., Eager, D.L., Galler, B.: Balanced Job Bound Analysis of Queueing Networks, in: Comm. ACM, 25(1982)2, pp.134–141;

    Google Scholar 

  87. Eager, D.L., Sevcik, K.C.: Performance Bound Hierarchies for Queueing Networks, in: ACM Trans. Comp. Syst., 1(1983), pp.99–115

    Google Scholar 

  88. see chapter 6.1.2.2

    Google Scholar 

  89. Graves, S.C., Whitney, D.E.: A Mathematical Programming Procedure for Equipment Selection and System Evaluation in Programming Assembly, in: Proc. 18th IEEE Conf. on Decision and Control, Fort Lauderdale 1979, p.531

    Google Scholar 

  90. Graves, S.C., Whitney, D.E.: A Mathematical Programming Procedure for Equipment Selection and System Evaluation in Programming Assembly, in: Proc. 18th IEEE Conf. on Decision and Control, Fort Lauderdale 1979, S.532–533; Note that in the presented Lagrangian Function (6) the right hand side of the relaxed constraint is missing.

    Google Scholar 

  91. see chapter 7.5 for an alternative approach

    Google Scholar 

  92. Graves, S.C., Lamar, B.W.: A Mathematical Programming Procedure for Manufacturing System Design and Evaluation, in: Proc. IEEE Int. Conf. on Cir. and Comput., 1980, p.1147

    Google Scholar 

  93. Graves, S.C., Lamar, B.W.: A Mathematical Programming Procedure for Manufacturing System Design and Evaluation, in: Proc. IEEE Int. Conf. on Cir. and Comput., 1980, p.1147

    Google Scholar 

  94. for a more detailed description of the algorithm see: Graves, S.C., Lamar, B.W.: A Mathematical Programming Procedure for Manufacturing System Design and Evaluation, in: Proc. IEEE Int. Conf. on Cir. and Comput., 1980, p.1148–1149;

    Google Scholar 

  95. Graves, S.C., Lamar, B.W.: An Integer Programming Procedure for Assembly System Design Problems, in: OR, 31(1983)3, p.531–537

    Google Scholar 

  96. see chapter 7.5 for an alternative approach

    Google Scholar 

  97. see chapter for example chapter 8.1.1.1 or 8.1.1.2

    Google Scholar 

  98. Erlenkotter, D.: A comparative study of approaches to dynamic location problems, in: EJOR, 6(1981), p. 135

    Google Scholar 

  99. Held, M., Karp, R.M.: The traveling salesman problem and minimum spanning trees, in: Mathematical Programming, 1(1971), pp.6–25

    Google Scholar 

  100. Held, M., Wolfe, P., Crowder, H.D.: Validation of subgradient optimization, in: Mathematical Programming, 6(1974), pp.62–88

    Google Scholar 

  101. Fisher, M.L.: The Lagrangian Relaxation Method for solving Integer Programming Problems, in: Management Science, 27(1981)1, p.8

    Google Scholar 

  102. Fisher, M.L., Northup, W.D., Shapiro, J.F.: Using Duality to solve Discrete Optimization Problems: Theory and Computational Experience, in: Mathematical Programming Study, 3(1975), pp.76–79

    Google Scholar 

  103. Shapiro, J.F.: A Survey of Lagrangian Techniques for Discrete Optimization, in: Annals of Discrete Mathematics, 5(1979), pp.132–135

    Google Scholar 

  104. Geoffrion, A.M.: Lagrangian Relaxation for Integer Prgramming, in: Mathematical Programming Study, 2(1974), pp.82–114

    Google Scholar 

  105. For a description of greedy algorithms see chapter 6.1.1.3

    Google Scholar 

  106. The variable in square brackets [] is rounded off to the next higher integer value.

    Google Scholar 

  107. The variable in square brackets [] is rounded off to the next higher integer value.

    Google Scholar 

  108. see results in Appendix D

    Google Scholar 

  109. For a more in-depth discussion on this subject, see chapter 7.3

    Google Scholar 

  110. Jacobsen, S.K.: Heuristic solution to dynamic plant location problems, in: M. Roubens (Ed.), Advances in Operation Research, Amsterdam 1977, pp.207–211

    Google Scholar 

  111. Jacobsen, S.K.: Heuristic solution to dynamic plant location problems, in: M. Roubens (Ed.), Advances in Operation Research, Amsterdam 1977, p.209

    Google Scholar 

  112. Jacobsen, S.K.: Heuristic solution to dynamic plant location problems, in: M. Roubens (Ed.), Advances in Operation Research, Amsterdam 1977, p.208

    Google Scholar 

  113. For a discussion on the priciples of the algorithm see chapter 8.3.1.3.

    Google Scholar 

  114. The variable in square brackets [] is rounded to the next higher integer value.

    Google Scholar 

  115. For a detailed description on ABA-bounds see for example Zahorjan, J., Sevcik, K.C., Eager, D.L., Galler, B.: Balanced Job Bound Analysis of Queueing Networks, in: Comm. ACM, 25(1982)2, pp. 134–141

    Google Scholar 

  116. see chapter 8.3.1.3

    Google Scholar 

  117. Suri, R.: A Concept of Monotonicity and Its Characterization for Closed Queueing Networks, in: OR, 33(1985)3, pp.606–624; See also chapter 6.1.2.2.3 for an overview on the properties of the throughput function.

    Google Scholar 

  118. Shanthikumar, J.G., Yao, D.: Second-Order Properties of the Throughput of a Closed Queueing Network, in: Mathematics of OR, 13(1988)3, p.525; See also chapter 6.1.2.2.3 for an overview on the properties of the throughput function.

    Google Scholar 

  119. see chapter 6.1.2.2

    Google Scholar 

  120. Cost minimal flow fractions q* arc those fractions which arc cost minimal under the considerations of the given constraints.

    Google Scholar 

  121. Shanthikumar, J.G., Yao, D.: Second-Order Properties of the Throughput of a Closed Queueing Network, in: Mathematics of OR, 13(1988)3, p.525; See also chapter 6.1.2.2.3 for an overview on the properties of the throughput function.

    Google Scholar 

  122. Moore, C.G.: Network Models for Large-Scale Time-Sharing Systems, Technical Report No.71–1, Department of Industrial Engineering, University of Michigan, Ann Arbor 1971, pp.47–52

    Google Scholar 

  123. Bruell, S.C., Balbo, G.: Computational Algorithms for Closed Queueing Networks, New York and Oxford 1980, p.52

    Google Scholar 

  124. Lazowska, E.D., Zahorjan, J., Graham, G.S., Sevcik, K.C.: Quantitative System Performance Computer System Analysis Using Queueing Network Models, Englewood Cliffs 1984, p.53

    Google Scholar 

  125. Shanthikumar, J.G.: On the superiority of balanced load in a flexible manufacturing system, technical report, Department of IE & OR, Syracuse University, New York, 1982, p.4

    Google Scholar 

  126. Note that the objective function in the above model considers the average operating costs for one part instead of all operating costs. This simplification is due to the fact that the production rate Rmin is constant.

    Google Scholar 

  127. see chapter 6.1.2.2

    Google Scholar 

  128. Whitney, C.K., Suri, R.: Algorithms for Part and Machine Selection in Flexible Manufacturing Systems, in: Annals of OR, 3(1985), p.243

    Google Scholar 

  129. Whitney, CK., Suri, R.: Algorithms for Part and Machine Selection in Flexible Manufacturing Systems, in: Annals of OR, 3(1985), p.252

    Google Scholar 

  130. Whitney, C.K., Suri, R.: Algorithms for Part and Machine Selection in Flexible Manufacturing Systems, in: Annals of OR, 3(1985), p.246

    Google Scholar 

  131. Whitney, C.K., Gaul, T.S.: Sequential Decision Procedures for Batching and Balancing in Flexible Manufacturing Systems, in: Annals of OR, 3(1985), pp.301–316

    Google Scholar 

  132. for a more detailed description of the Algorithm see: Whitney, C.K., Suri, R.: Algorithms for Part and Machine Selection in Flexible Manufacturing Systems, in: Annals of OR, 3(1985), pp.257–260

    Google Scholar 

  133. Whitney, C.K., Gaul, T.S.: Sequential Decision Procedures for Batching and Balancing in Flexible Manufacturing Systems, in: Annals of OR, 3(1985), pp.301–316

    Google Scholar 

  134. Sarin, S.C., Chen, C.S.: A Mathematical Model for Manufacturing System Selection, in: Flexible Manufacturing Systems: Methods and Studies, Ed.: A. Kusiak, Elsevier Science Publishers B.V. (North Holland) 1986, p.102

    Google Scholar 

  135. King, J.R.: Machine-Component Group Formation in Group Technology, presented at the Vth Intern. Conf. on Production Research, Amsterdam Aug. 1979, in: OMEGA, 8(1980)2, pp.193–199

    Google Scholar 

  136. King, J.R., Nakornchai, V.: Machine-Component Group Formation in Group Technology: Review and Extension, in: UPR, 20(1982)2, pp.117–133

    Google Scholar 

  137. Sarin, S.C., Chen, CS.: A Mathematical Model for Manufacturing System Selection, in: Flexible Manufacturing Systems: Methods and Studies, Ed. A. Kusiak, Elsevier Science Publishers B.V. (North Holland) 1986, p. 105

    Google Scholar 

  138. see chapter 4.2.1

    Google Scholar 

  139. Sarin, S.C., Chen, CS.: A Mathematical Model for Manufacturing System Selection, in: Flexible Manufacturing Systems: Methods and Studies, Ed. A. Kusiak, Elsevier Science Publishers B.V. (North Holland) 1986, p.100

    Google Scholar 

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Tetzlaff, U.A.W. (1990). Models for the optimal design of flexible manufacturing systems. In: Optimal Design of Flexible Manufacturing Systems. Contributions to Management Science. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-50317-7_8

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  • DOI: https://doi.org/10.1007/978-3-642-50317-7_8

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