A simulated annealing algorithm for the robust decomposition of temporal horizons in production planning problems

Main Article Content

José Fidel Torres Delgado
Mario César Vélez Gallego

Keywords

production planning, simulated annealing.

Abstract

The problem of robust decomposition of temporal horizons in production planning was first introduced by Torres [1]. Later, in [2], Torres suggests to start with an integer solution found by dynamic programming, and then to use a simulated annealing algorithm to improve it. According to [2], more needs to be known about the impact of the control parameters in the simulated annealing algorithm, and their sensitivity with respect to the quality of the solutions. In this work we develop this idea and analyze in depth the ability of the simulated annealing algorithm to improve the initial solution. As a result of the computational experiments conducted, we determined that the cooling scheme and the cooling rate have significant effect on the quality of the final solution. It was also established that the solution found depends strongly on the characteristics of the operations plan, finding better solutions for plans with shorter temporal horizons.

MSC: 62-XX, 62Kxx, 68Uxx, 65Kxx

Downloads

Download data is not yet available.
Abstract 774 | PDF (Español) Downloads 907

References

[1] F. Torres. Un systeme interactif d’aide a la decision pour la regulation de charges de travail dans les ateliers. Rapport LAAS N◦ 95363, 1995.

[2] F. Torres. Robust division of temporal horizons in production planning. IEEE, International Conference on Systems, Man and Cybernetics, ISBN 0–7803– 6583-6, 1, 323–327 (2000).

[3] J. Wallace Hopp and Mark L. Spearman. Factory physics second edition, ISBN 978–0256247954. McGraw Hill, 2000.

[4] J. Orlicky. Material requirement planning, ISBN 0070477086.McGraw Hill, 1975.

[5] S. Kirkpatrick, C. D. Gelatt and M. P. Vecchi. Optimization by simulated annealing. Science, ISSN 0036–8075, 220(4598), 671–680 (1983).

[6] A. Castro y F. Torres. Descomposición robusta de horizontes temporales en problemas de regulación agregada de cargas de trabajo para múltiples recursos. Memos de Investigación, Universidad de los Andes, 2003.

[7] C. Mantilla y F. Torres. Regulación detallada y robusta de la carga de trabajo por medio de técnicas de optimización combinatoria. Memos de Investigación, Universidad de los Andes, 2001.

[8] A. Desrochers and R. Al-Jaar. Applications of Petri nets in manufacturing systems: Modeling, control, and performance analysis. IEEE, ISSN 0272–1708, 1994.

[9] S. Sait and H. Youssef. Iterative computer algorithms with applications in engineering. IEEE, ISBN 978–0–7695–0100–0, 1999.

[10] J. Y. Sridhar and C. Rajendran. Scheduling in a cellular manufacturing system: a simulated annealing approach. International Journal of Production Research, ISSN 0020–7543, 31(12), 2927–2945 (1993).

[11] J. M. Varanelli and J. P. Cohoon. A two stages simulated annealing methodology. Proceedings of the 5th Great Lakes Symposium on VLSI, 50–53 (1995).

[12] D. Montgomery. Design and analysis of experiments, ISBN 0–471–48735–X. John Wiley & Sons, 1991.

[13] S. K. Mukhopadhyay, M. K. Singh and R. Srivastava. FMS machine loading: a simulated annealing approach. International Journal of Production Research, ISSN 0020–7543, 36(3), 1529–1547 (1998).

[14] O. Davies and P. Goldsmith. Statistical methods in research and production, ISBN 978–0582450875. Longman Scientific & Technical, 1988.