1. bookVolume 19 (2018): Edizione 3 (September 2018)
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1407-6179
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20 Mar 2000
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4 volte all'anno
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The Combination of Discrete-Event Simulation and Genetic Algorithm for Solving the Stochastic Multi-Product Inventory Optimization Problem

Pubblicato online: 26 Jun 2018
Volume & Edizione: Volume 19 (2018) - Edizione 3 (September 2018)
Pagine: 233 - 243
Dettagli della rivista
License
Formato
Rivista
eISSN
1407-6179
Prima pubblicazione
20 Mar 2000
Frequenza di pubblicazione
4 volte all'anno
Lingue
Inglese

1. Alizadeh, M., Eskandari, H., Sajadifar, S. and Geiger, C. (2011) Analysing a stochastic inventory system for deteriorating items with stochastic lead time using simulation modelling. In: Proceedings of the 2011 winter simulation conference. Winter Simulation Conference, pp. 1650-1662.Search in Google Scholar

2. Altiparmak, F., Gen, M., Lin, L. and Paksoy, T. (2006) A genetic algorithm approach for multi- objective optimization of supply chain networks. Computers & industrial engineering, 51(1), 196–215. DOI:10.1016/j.cie.2006.07.01110.1016/j.cie.2006.07.011Apri DOISearch in Google Scholar

3. Bijvank, M. and Vis, I.F.A. (2011) Lost-sales inventory theory: A review. European Journal of Operational Research, 215(1), 1 – 13. DOI:10.1016/j.ejor.2011.02.00410.1016/j.ejor.2011.02.004Apri DOISearch in Google Scholar

4. Bookbinder, J.H. and Cakanyildirim, M. (1999) Random lead times and expedited orders in (Q, r) inventory systems. European Journal of Operational Research, 115(2), 300–313.10.1016/S0377-2217(98)00304-XSearch in Google Scholar

5. Brandel, W. (2009) Free Up Cash!; Inventory optimization save working capital in tough times. Computerworld. [online] www.computerworld.com. Available at: https://www.computerworld.com/article/2549533/it-industry/free-up-cash [Accessed 9 Mar. 2018]Search in Google Scholar

6. Fortin, F.A., Rainville, F.M.D., Gardner, M.A., Parizeau, M. and Gagné, C. (2012) DEAP: Evolutionary algorithms made easy. Journal of Machine Learning Research, 13(Jul), 2171–2175.Search in Google Scholar

7. Holland, J.H. (1975) Adaptation in natural and artificial systems. Ann Arbor, MI: University of Michigan Press.Search in Google Scholar

8. Hopp, W.H. and Spearman M.L. (2008) Factory Physics. Waveland Press.Search in Google Scholar

9. Juan, A.A., Faulin, J., Grasman, S.E., Rabe, M. and Figueria, G. (2015) A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspective, 2, 62–72. DOI:10.1016/j.orp.2015.03.00110.1016/j.orp.2015.03.001Apri DOISearch in Google Scholar

10. Juan, A.A., Grasman, S.E., Caceres-Cruz, J. and Bektaş, T. (2014) A simheuristic algorithm for the single-period stochastic inventory-routing problem with stock-outs. Simulation Modelling Practice and Theory, 46, 40–52. DOI:10.1016/j.simpat.2013.11.00810.1016/j.simpat.2013.11.008Search in Google Scholar

11. Kotz, S. and Van Dorp, R.J. (2004) Beyond Beta: Other Continuous Families of Distributions with Bounded Support and Applications. World Scientific.10.1142/5720Search in Google Scholar

12. Kouki, C., Jemai, K. and Minner, S. (2015) A Lost Sales (r,Q) Inventory Control Model for Perishables with Fixed Lifetime and Lead Time. Int. J. Production Economics, 168, 143–157.10.1016/j.ijpe.2015.06.010Search in Google Scholar

13. Luke, S. (2015) Essentials of Metaheuristics. A Set of Undergraduate Lecture Notes. Second Edition, 2.2, pp. 31-55.Search in Google Scholar

14. Man, K.F., Tang, K.S. and Kwong, S. (1996) Genetic algorithms: concepts and applications [in engineering design]. IEEE transactions on Industrial Electronics, 43(5), 519–534. DOI:10.1109/41.53860910.1109/41.538609Apri DOISearch in Google Scholar

15. Michalewicz, Z. (1996) Evolution strategies and other methods. In: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin, Heidelberg, pp. 159-177.10.1007/978-3-662-03315-9_9Search in Google Scholar

16. Miller, B.L. and Goldberg, D.E. (1995) Genetic algorithms, tournament selection, and the effects of noise. Complex systems, 9(3), pp. 193–212. DOI:10.1162/evco.1996.4.2.11310.1162/evco.1996.4.2.113Apri DOISearch in Google Scholar

17. Min, Z. and Lindu, Z. (2016) Arena Simulation of Multi-Level Medicine Inventory Control in Hospital Pharmacy. International Journal of Hybrid Information Technology, 9(6), pp.283-294.10.14257/ijhit.2016.9.6.25Search in Google Scholar

18. Pasandideh, S.H.R. and Niaki, S.T.A. (2008) A genetic algorithm approach to optimize a multi- products EPQ model with discrete delivery orders and constrained space. Applied Mathematics and Computation, 195(2), 506–514. DOI:10.1016/j.amc.2007.05.00710.1016/j.amc.2007.05.007Apri DOISearch in Google Scholar

19. Pidd, M. (1998) Computer simulation in management science. ISBN:0471979317.Search in Google Scholar

20. Scherfke, S. (2014) Discrete-event simulation with SimPy. OFFIS – Institute for Information Technologie, USA.Search in Google Scholar

21. Stack Exchange (2017) Why do we use binary encoding when it seems so inefficient? [online] softwareengineering.stackexchange.com. Available at: https://softwareengineering.stackexchange.com/questions/339705/why-do-we-use-binary-encoding-when-it-seems-so-inefficient/339709 [Accessed 8 Mar. 2018].Search in Google Scholar

22. Subramanian, D., Pekny, J.F. and Gintaras, V.R. (2000) A simulation—optimization framework for addressing combinatorial and stochastic aspects of an R&D pipeline management problem. Computers & Chemical Engineering, 24(2-7), 1005–1011.10.1016/S0098-1354(00)00535-4Search in Google Scholar

23. Sinaga, S., Pertiwi, L.S. and Ardian, T. (2016) Inventory Simulation Optimization under Non Stationary Demand. International Journal of Applied Engineering Research, 11(1), pp. 524-529.Search in Google Scholar

24. Williams, E.A. and Crossley, W.A. (1998) Empirically-derived population size and mutation rate guidelines for a genetic algorithm with uniform crossover. In: soft computing in engineering design and manufacturing. Springer, London, pp. 163-172.10.1007/978-1-4471-0427-8_18Search in Google Scholar

25. Yeh, W.C. and Chuang, M.C. (2011) Using multi-objective genetic algorithm for partner selection in green supply chain problems. Expert Systems with applications, 38(4), 4244–4253. DOI:10.1016/j.eswa.2010.09.09110.1016/j.eswa.2010.09.091Apri DOISearch in Google Scholar

26. Zipkin, P.H. (2000) Foundations of inventory management. McGrawHill. ISBN-13:978-0256113792. Zvirgzdiņa, B. and Tolujew, J. (2016) Experience in Optimization of Discrete Rate Models Using ExtendSim Optimizer. In: 9th International Doctoral Students Workshop on Logistics, June, 2016. Magdeburg, Otto von Guericke University, pp. 95-100.Search in Google Scholar

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