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Heuristic solution approaches for combined-job sequencing and machine loading problem in flexible manufacturing systems

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Abstract

Job sequencing and machine loading are two vital and interrelated production planning problems in flexible manufacturing systems (FMSs). In this research, attempts have been made to address the combined job sequencing and machine loading problem using minimization of system unbalance and maximization of throughput as objective functions, while satisfying the constraints related to available machining time and tool slots. This research describes two heuristics to deal with the problems. Heuristic I uses predetermined fixed job sequencing rules as inputs for operation allocation decision on machines, whereas heuristic II uses genetic algorithm based approach for simultaneously addressing job sequences and operation machine allocation issues. Performance of these heuristics has been tested on problems representing three different FMS scenarios. Heuristic II (Genetic algorithm based) has been found more efficient and outperformed heuristic I in terms of solution quality.

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References

  1. Sawik TJ (1989) Production scheduling in flexible manufacturing system. Syst Sci 15(4):113–124

    MATH  Google Scholar 

  2. Gyampah KA, Meredith JR (1996) A simulation study of FMS tool allocation procedures. J Manuf Syst 15(6):419–431

    Google Scholar 

  3. Stecke KE (1983) Formulation and solution of non-linear integer production planning problem for flexible manufacturing system. Manage Sci 29(3):273–288

    MATH  Google Scholar 

  4. Van Looveren AJ, Gelders JLF, Van Wessenhove LN (1986) A review of FMS planning models. In: Kusiak A (ed) Modelling and design of flexible manufacturing system. Elsevier Science, Amsterdam pp 3–31

    Google Scholar 

  5. Berrada M, Stecke KE (1986) A branch and bound approach for machine load balancing in flexible manufacturing system. Manage Sci 32(10):1316–1335

    MATH  Google Scholar 

  6. Suri R, Whiney CK (1984) Design support requirements in flexible manufacturing. J Manuf Syst 3(1):61–69

    Google Scholar 

  7. Mukhopadhyay SK, Midha S, Murlikrishna V (1992) A heuristic procedure for loadingp in flexible manufacturing systems. Int J Prod Res 30(9):2213–2228

    Google Scholar 

  8. Tiwari MK, Hazarika B, Vidyarthi NK, Jaggi P, Mukhopadhyay SK (1997) A heuristic solution approach to the machine loading problem of an FMS and its Petri net model. Int J Prod Res 35(8):2269–2284

    Article  MATH  Google Scholar 

  9. Shankar K, Tzen YJJ (1985) A loading and dispatching problem in a random FMS. Int J Prod Res 23(3):579–593

    Google Scholar 

  10. Liang M, Dutta SP (1993) An integrated approach to part selection and machine loading problem in a class of flexible manufacturing systems. Eur J Oper Res 67:387–404

    Article  MATH  Google Scholar 

  11. Lashkari RS, Dutta SP, Padhe AM (1987) A new formulation of operation allocation problem in flexible manufacturing system and computational Experience. Int J Prod Res 25(9):1267–1283

    MATH  Google Scholar 

  12. Mukhopadhyay SK, Tiwari MK (1995) Solving machine loading problems of FMS using conjoint measurement. Proc 13th Int Conference of Production Research. Jerusalem, pp 74–76

  13. Kusiak A (1983) Loading models in flexible manufacturing system. Proc VIIth Int Conference on Production Research. Windsor, Ontario, pp 641–647

  14. Chen YJ, Askin RG (1990) A multiobjective evaluation of flexible manufacturing system batching, loading and tool configuration problems. Int J Prod Res 28(12):2171–2187

    Google Scholar 

  15. Sarin SC, Chen CS (1987) Machine loading and allocation problem in a flexible manufacturing system. Int J Prod Res 25(7):1081–1094

    Google Scholar 

  16. O’Grady PJ, Menon U (1987) Loading a flexible manufacturing system. Int J Prod Res 25(7):1053–1068

    Google Scholar 

  17. Ram B, Sarin S, Chen CS (1990) A model and a solution approach for the machine loading and tool allocation problem in flexible manufacturing system. Int J Prod Res 28(4):637–645

    Google Scholar 

  18. Rajagopalan S (1986) Formulation and heuristic solutions for past grouping and tool loading in flexible manufacturing system. In: Stecke KE, Suri S (eds) Proc Second ORSA/TIMS Conference on FMS. Elsevier, Amsterdam, pp 311–320

  19. Escudero LF (1989) An exact algorithm for part input sequencing and scheduling with side constraints in FMS. Int J Flex Manuf Syst 1(2):143–174

    Article  Google Scholar 

  20. Kumar P, Singh N, Tiwari NK (1989) Multicriterion aAnalysis of the loading problem in flexible manufacturing systems using min-max approach. Int J Adv Manuf Technol 2(2):13–23

    Google Scholar 

  21. Ammons JC, Lofgren CB, McGinnis LF (1985) A large scale machine loading problem in flexible assembly. Ann Oper Res 3:319–322

    Article  Google Scholar 

  22. Jain S, Barber K, Osterfled D (1989) Expert simulation for on-line Scheduling. Proc 1989 Winter Simulation Conference, pp 930–935

  23. Kim MH, Kim Y-D (1994) Simulation based real time scheduling in a flexible manufacturing system. J Manuf Syst 13(2):85–93

    Google Scholar 

  24. Choi RH, Malstrom EM (1988) Evaluation of traditional work scheduling rules in a flexible manufacturing system with a physical simulator. J Manuf Syst 7(1):33–45

    Article  Google Scholar 

  25. Gyampah KA, Meredith JR (1996) A simulation study of FMS tool allocation procedures. J Manuf Syst 15(6):419–431

    Google Scholar 

  26. Mukhopadhyay SK, Maiti B, Garg S (1991) Heuristic solution to the scheduling problems in flexible manufacturing systems. Int J Prod Res 29(10):2003–2024

    MATH  Google Scholar 

  27. Moreno AA, Ding FY (1993) Heuristics for the FMS loading and part type selection problems. Int J Flex Manuf Syst 5:287–300

    Article  Google Scholar 

  28. Barash MM (1978) Speculation on the future of numerical controls. American Society of Manuf Engineers Conference, Paper 78 – WA/DSC-9

  29. Ito Y (1981) Japanese FMS - Present and a future view. Handouts of seminars on FMS, (ROC)

  30. Goldberg DE (1989) Genetic algorithms in search optimization and machine learning. Addison-Wesley, Boston

    MATH  Google Scholar 

  31. Michalwicz Z (1992) Genetic algorithms + data structure = eEvolution programs. Springer, Berlin Heidelberg New York

    Google Scholar 

  32. Grefenstette JJ, Gopal R, Rormatia B, Vengucht D (1985) Genetic algorithms for travelling salesman problem. First Int Conference on Genetic Algorithms and Their Applications, Lawrence Erlbaum Associate, Hilsdale

  33. Laszewski GV (1991) Intelligent structural operations for the K-way graph partitioning problem. Proc Int Conference on Genetic Algorithm and Their Applications, pp 45–52

  34. Davis L (1985) Job shop scheduling with genetic algorithms. Proc the Int Conference on Genetic Algorithms and Their Applications, Carnegie Mellon University, Pittsburgh, pp 136–140

  35. Clevland CA, Smith SF (1989) Using genetic algorithms to scheduling flowshop releases. Proc Third Int Conference on Genetic Algorithm and their Applications. Kaufmann, Palo Atto, pp 160–169

  36. Chen CL, Vempatti VS, Aljber N (1995) An application of genetic algorithm for flowshop problem. Eur J Oper Res 80:385–396

    Google Scholar 

  37. Jain AK, Elmaraghy HA (1997) Production scheduling/rescheduling in flexible manufacturing. Int J Prod Res 35(1):281–309

    Article  MATH  Google Scholar 

  38. Lee CY, Piramuthu S, Tsai YK (1997) Job shop scheduling with genetic algorithm and machine learning. Int J Prod Res 35(4):1171–1191

    Article  MATH  Google Scholar 

  39. Herrmann JW, Lee CY (1995) Solving a class scheduling problem with a genetic algorithm. ORSA J Comput 7:443–452

    MATH  Google Scholar 

  40. Gupta M, Gupta Y, Gupta A (1993) Minimizing flowtime variance in single machine system using genetic algorithm. Eur J Operl Res 70:289–303

    Article  MATH  Google Scholar 

  41. Fourman MP (1985) Comparison of symbolic layout using genetic algorithm. Proc First Int Conference on Genetic Algorithms and Their Applications. Erlbaum, Hilsdale, NJ, pp 141–155

  42. Grefenstette JJ (1989) A system for learning control strategies with genetic algorithm. Proc 3rd Int Conference on Genetic Algorithm, Morogan/Kaufmann, Palo Atto

  43. Gupta Y, Gupta M, Kumar A, Sundram C (1996) A genetic algorithm-based approach to cell composition and layout design problems. Int J Prod Res 34(2):447–482

    MATH  Google Scholar 

  44. Holand HH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Detroit MI

    Google Scholar 

  45. Goldberg DE, Lingle R (1985) Alleles, loci and the travelling salesman problem. Proc 1st Int Conference on Genetic Algorithms and their Applications. Lawrence Elrbaum, Hilsdale, NJ, pp 931–940

  46. Sawaka M, Kato K, Muri T (1996) Flexible scheduling in a machining centre through genetic algorithm. Comput Ind Eng 30(4):931–940

    Article  Google Scholar 

  47. Starkwather T, McDaniel S, Mathias K, Whitley C, Whitely C (1991) A comparison of genetic sequencing operators. Proc 4th Int Conference on Genetic Algorithms. Kaufmann, Los Altos Ca, pp 69–76

  48. Davis L (1991) Handbook of genetic algorithms. Reinhold, New York

    Google Scholar 

  49. Olive IM, Smith DJ, Holland JRC (1987) A study of permutation crossover operators on the travelling salesman problem. Proc Second Int conference on Genetic Algorithms, pp 224–230

  50. Herdy M (1991) Application of the evaluation strategy to descrete optimization problem. Proc First Int Conference: Parallel Problem Solving from Nature (PPSN), Lecture Notes in Computer Science, 496. Springer, Berlin Heidelberg New York, pp 188–192

  51. Grefenstette JJ (1986) Optimization of control parameters for genetic algorithms. IEEE Trans Man Mach Cybern 16(1):122–128

    Google Scholar 

  52. De Jong KA, Spears WM (1985) Using genetic algorithms to solve NP-complete problems. Earlbaum, Hilsdale, NJ, pp 124–132

    Google Scholar 

  53. Schaffe JD, Caruana RA, Eshelman LJ, Das R (1989) A study of control parameters affecting on-line performance of genetic algorithms for function optimization. Proc Third Int Conference on Genetic Algorithms and their Application. Kaufmann, Palo Atto, CA, pp 51–60

  54. Pathak R, Zaveri ZS (1993) Specifying critical inputs in an genetic driven decision support system. An Automated Facility Working Paper, University of Kentuki, Lexington

  55. Stecke KE, Solberg JJ (1981) Loading and control policies for a flexible manuf systems. Int J Prod Res 19(5):481–490

    Google Scholar 

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Authors and Affiliations

  1. Department of manufacturing Engineering, National Institute of Foundry and Forge Technology (NIFFT), Ranchi, 834003, India

    M. K. Tiwari

  2. Department of Production Engineering, Jadavpur University, Kolkata, India

    J. Saha

  3. National Institute of Industrial Engineering (formerly known as NITIE), Vihar Lake, P.O.: NITIE, Powai, Mumbai, 400087, India

    S. K. Mukhopadhyay

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  1. M. K. Tiwari
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  2. J. Saha
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  3. S. K. Mukhopadhyay
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Correspondence to M. K. Tiwari.

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Tiwari, M.K., Saha, J. & Mukhopadhyay, S.K. Heuristic solution approaches for combined-job sequencing and machine loading problem in flexible manufacturing systems. Int J Adv Manuf Technol 31, 716–730 (2007). https://doi.org/10.1007/s00170-005-0259-7

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  • DOI: https://doi.org/10.1007/s00170-005-0259-7

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