Revista de Matemática: Teoría y Aplicaciones ISSN Impreso: 1409-2433 ISSN electrónico: 2215-3373

OAI: https://revistas.ucr.ac.cr/index.php/matematica/oai
Simulated Annealing–Golden section algorithm for the multiproduct replenishment problem with stochastic demand.
PDF (Español (España))

Keywords

Multi-item inventory problem
joint replenishment problem
simulated annealing
golden section
Problemas de inventario multiproducto
problema de reaprovisionamiento conjunto
recocido simulado
sección dorada

How to Cite

Hernández González, S., Gutiérrez Andrade, M. Á., & De los Cobos Silva, S. (2010). Simulated Annealing–Golden section algorithm for the multiproduct replenishment problem with stochastic demand. Revista De Matemática: Teoría Y Aplicaciones, 17(2), 121–141. https://doi.org/10.15517/rmta.v17i2.2124

Abstract

The joint replenishment problem (JRP) has been studied for over 30 years and there are both heuristic and exact algorithms to determine the frequency of orders and fundamental cycle; in recent years it has been considered the model with stochastic demand. If we assume a behavior of normal distribution for the demand, we may obtain a non linear mixed-integer programming for costs, for which only is reported one heuristic solving method. In this paper we propose a simulated annealing algorithm with golden section for one-dimensional search in order to solve the JRP considering a normal distribution demand. Its performance is compared with the reported heuristic method. The results showed that the new algorithm obtains lower costs.

https://doi.org/10.15517/rmta.v17i2.2124
PDF (Español (España))

References

Atkins, D.; Iyogun, P. (1988) “Periodic versus “can-order” policies for coordinated multi-item inventory systems”, Management Science 34(6): 791-796.

Barr, R.; Golden, B. L.; Kelly, J.; Resende, G.C; Stewart, W. R. JR. (1995) “Designing and reporting on computational experiments with metaheuristics”, Journal of Heuristics 1: 9–32.

Bazaraa, M.; Sherali, H.; Shetty, C.M. (2006) Nonlinear Programming. John Wiley and Sons, New York.

Eynan, A.; Kropp, D. (1998) “Periodic review and joint replenishment in stochastic demand environments”, IEEE Transactions 30(11): 1025–1033.

Eynan, A.; Kropp, D. (2007) “Effective and simple EOQ-like solutions for stochastic demand periodic review systems”, European Journal of Operational Research 180(31): 1135–1143.

Fung, R. Y. K.; Ma, X.; Lau, H. C. W. (2001) “(T, S) Policy for coordinated inventory replenishment systems under compound poisson demand”, Production Planning and Control 12(6): 575–583.

Goyal, S. K. (1974) “Determination of optimum packaging frequency for items jointly replenished”, Management Science 21: 436–443.

Johnson, D.; Aragon, C.; McGeoch, L.; Schevon, C. (1989) “Optimization by simulated annealing: an experimental evaluation; part I, graph partitioning”, Operations Research 37(6): 865–892.

Khouja, M.; Goyal, S. (2008) “A review of the joint replenishment problem literature: 1989-2005”, European Journal of Operational Research 186(1): 1–16.

Kirkpatrick, S.; Gellat, C. D.; Vecci, M. P. (1983) “Optimization by simulated annealing”, Science 220: 671–680.

Myers, R.H.; Montgomery, D C. (2002), Response Surface Methodology: Process and Product Optimization Using Designed Experiments. John Wiley and Sons, New York.

Pantumsinchai, P.A. (1992) “Comparison of three joint ordering inventory policies”, Decision Sciences23: 111–127.

Silver, E.; Peterson, R. (1985) Decision Systems for Inventory Management and Production Planning. John Wiley and Sons, New York.

Viswanathan, S. (1997) “Periodic review (s,S) policies for joint replenishment inventory systems”, Management Science 43(10): 1447–1454.

Comments

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Copyright (c) 2010 Revista de Matemática: Teoría y Aplicaciones

Downloads

Download data is not yet available.