This paper describes an approach to manufacturing planning that seeks to integrate both process planning and scheduling. We show that separating these two related tasks, as is the common practice, can impose constraints that substantially reduce the quality of the final schedule. These constraints arise from premature decisions regarding operation sequence and allocation of manufacturing resources. Having formulated an integrated process planning and scheduling problem, we describe a solution technique based on simulated annealing. We compare this approach with others reported in the literature, considering both their generality and performance. In particular, we perform a detailed empirical comparison between simulated annealing and the popular technique of dispatching rules. Our results, achieved with two distinct sets of example problems, show that simulated annealing can produce solutions of significantly higher quality than those achieved through a published dispatching rule approach.
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References
Applegate, D. and Cook, W. (1991) A computational study of the job-shop scheduling problem. ORSA Journal on Computing, 3 (2), 149–156.
Barker, J. R. and McMahon, G. B. (1985) Scheduling the general job-shop. Management Science, 31 (5), 594–598.
Blackstone, J. H., Philips, D. T. and Hogg, G. L. (1982) A state-of-the-art survey of dispatching rules for manufacturing job shop operations. International Journal of Production Research, 20 (1), 27–45.
Brandimarte, P. (1992) Neighbourhood search-based optimization algorithms for production scheduling: a survey. Computer-Integrated Manufacturing Systems, 5 (2), 167–176.
Brandimarte, P. and Calderini, M. (1992) Integrated process planning and shop scheduling by local search algorithms. IFIP Transactions B: Applications in Technology, 7, 257–276.
Carlier, J. and Pinson, E. (1989) An algorithm for solving the job-shop problem. Management Science, 35 (2), 164–176.
Cerny, V. (1985) Thermodynamical approach to the travelling salesman problem. Journal of Optimisation Theory and Applications, 45 (1), 41–51.
Charalambous, O. and Hindi, K. S. (1991) A review of artificial intelligence-based job-shop scheduling systems. Information and Decision Technologies, 17 (3), 189–202.
Cheng, T. C. E. and Sin, C. C. S. (1990) A state-of-the-art review of parallel-machine scheduling research. European Journal of Operational Research, 47 (3), 271–292.
Fisher, R. A. (1936) Statistical Methods for Research Workers, 6th edn, Oliver & Boyd, Edinburgh.
Glover, F. (1989) Tabu search Part I. ORSA Journal on Computing, 1 (3), 190–206.
Goldberg, D. E. (1989) Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA.
Holland, J. H. (1975) Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI.
Husbands, P. (1993) An ecosystems model for integrated production planning. International Journal of Computer Integrated Manufacturing, 6 (1–2), 74–86.
Ingber, L. and Rosen, B. (1992) Genetic algorithms and very fast simulated reannealing: a comparison. Mathematical and Computer Modelling, 16 (11), 87–100.
Iwata, K., Murotsu, Y., Oba, F. and Uemura, T. (1978) Optimization of selection of machine-tools, loading sequence of parts and machining conditions in job-shop type machining systems. Annals of the CIRP, 27 (1), 447–451.
Jiang, J.-C. (1991) IS: An intelligent scheduler for batch manufacturing systems. Computers and Industrial Engineering, 21 (1–4), 319–323.
Jones, M. S. and Russell, R. S. (1990) Multiple performance measures in the selection of a sequencing rule. International Journal of Operations and Production Management, 10 (8), 29–41.
Kerr, R. M. (1992) Expert systems in production scheduling: lessons from a failed implementation. Journal of Systems Software, 19 (2), 123–130.
Khoshnevis, B. and Qingmei Chen (1990) Integration of process planning and scheduling functions. Journal of Intelligent Manufacturing, 1, 165–176.
Kirkpatrick, S., Gelatt, C. D. and Vecchi, M. P. (1983) Optimization by simulated annealing. Science, 220, 671–690.
Lawler, E. L., Lenstra, J. K. and Rinnooy Kan, A. H. G. (1982) Recent developments in deterministic sequencing and scheduling: a survey, in Deterministic and Stochastic Scheduling: Proceedings of the NATO Advanced Study and Research Institute on Theoretical Approaches to Scheduling Problems, Dempster, M. A. H. et al. (eds), Reidel, Dordrecht, pp. 35–73.
Palmer, G. J. (1994) An integrated approach to manufacturing planning, PhD Thesis, University of Huddersfield, UK.
Potts, C. N. and Van Wassenhove, L. N. (1991) Single machine tardiness sequencing heuristics. IIE Transactions, 23 (4), 346–354.
Rinnooy Kan, A. H. G. (1976) Machine Scheduling Problems, Martinus Nijhoff, The Hague.
Rumelhart, D. E. and McClelland, J. L. (1986) Parallel Distributed Processing, Vol. 1, MIT Press, Cambridge, MA, pp. 287–288, 322–324.
Sundaram, R. M. and Fu, S.-S. (1988) Process planning and scheduling - a method of integration for productivity improvement. Computers and Industrial Engineering, 15 (1–4), 296–301.
Van Laarhoven, P. J. M., Aarts, E. H. L. and Lenstra, J. K. (1992) Job shop scheduling by simulated annealing. Operations Research, 40 (1), 113–125.
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Palmer, G.J. A simulated annealing approach to integrated production scheduling. J Intell Manuf 7, 163–176 (1996). https://doi.org/10.1007/BF00118077
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DOI: https://doi.org/10.1007/BF00118077