Analysis of an inventory model in perishable products applying Tabu and Montecarlo simulation metaheuristic algorithm

  • Xavier Jurado Mero Universidad de Guayaquil
  • Jorge Peña Universidad de Guayaquil
  • Kevin Veloz Villon Universidad de Guayaquil
  • Lorenzo Cevallos-Torres Universidad de Guayaquil
Keywords: Inventory Theory, Taboo Algorithm, Monte Carlo Algorithm, Simulation, Stocks, Perishable Products

Abstract

The present research work intends to provide an optimal solution to the inventory problems present in the bakery “El Chino”, given that in the last three years due to the reports sent to the local administrator, it was possible to show that it is unknown appropriate amount of thread production and its periodicity, generating a large number of stock of perishable products, which, to avoid a major loss before it expires, is sold at the price of production cost. Therefore, based on the information provided from the years 2017, 2018 and so far from 2019, the remaining months of the current year will be simulated, to project the amount of thread production for the year 2020, so it is proposed to optimize the cost of sales, the use of computer tools, simulation techniques, and application of mathematical, metaheuristic and stochastic models such as the Monte Carlo Algorithm and the Taboo algorithm, resulting in the appropriate amount of daily production, which will be presented to the local administrator

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Azadeh, A., & Maghsoudi, A. (2010). Optimization of production systems through integra-tion of computer simulation, design of experiment, and Tabu search: the case of a large steelmak-ing workshop. The International Journal of Advanced Manufacturing Technology, 48(5-8), 785-800.

Daniel Jaramillo Maya, Medellín 2013 “Diseño e implementación de un modelo de inventa-rios para los productos descentralizados en la compañía Avon Colombia ltda.” Enlace: https://repository.eafit.edu.co/bitstream/handle/10784/8280/Daniel_JaramilloMaya_2013.pdf?sequence=2

Freddy Andrés Pérez Mantilla, Fidel Torres, agosto 2014 “Modelos de inventarios con pro-ductos perecederos: revisión de literatura” Enlace: http://www.scielo.org.co/pdf/inge/v19n2/v19n2a01.pdf

John Willmer Escobar (Colombia), Rodrigo Linfati (Chile), Wilson Adarme Jaimes (Colombia), “Gestión de Inventarios para distribuidores de productos perecederos” ISSN Electronico 2145-9371, ISSN Impreso 0122-3461, Volumen 35, n.°1, enero - julio 2016

Diego Fernando Batero Manso, BOGOTÁ D.C. 2017,“modelo matemático multi-objetivo de ruteo e inventarios para la cadena de suministro de perecederos: caso sector fruticola”.

David Higuita-Alzate, Marisol Valencia-Cárdenas & Juan Carlos Correa-Morales, Septem-ber 6th, 2017. Combination forecasting method using Bayesian models and a metaheuristic, case study.

Medina, S. y García, J., Predicción de demanda de energía en Colombia mediante un sistema de inferencia difuso neuronal. Energética. 33, pp. 15-24, 2005. DOI: 10.15446/energetica

Keles, D., Scelle, J., Paraschiv, F. and Fichtner, W., Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks. Appl. Energy. 162, pp. 218-230, 2016.

Claveria, O. and Torra, S., Forecasting tourism demand to Catalonia: neural networks vs. time series models. Econ. Model. 36, pp. 220-228, 2014.

West, B., Welch, K. and Galecki, A., Linear mixed models: a practical guide using statistical software, first. 2006.

Valencia, M., Estimación en modelos lineales mixtos con datos continuos usando transfor-maciones y distribuciones no normales. Tesis de grado. Universidad Nacional de Colombia, Sede Medellín. [en línea]. Disponible en: http://www.bdigital.unal.edu.co/1862/1/71680093.2010.pdf, 2010.

Fei, X., Lu, C.-C. and Liu, K., A bayesian dynamic linear model approach for real-time short-term freeway travel time prediction. Transp. Res. Part C Emerg. Technol. 19(6), pp. 1306-1318, 2011. DOI: 10.1016/j.trc.2010.10.005

Sakauchi, T., Applying bayesian forecasting to predict new customers’ heating oil demand, 2011.

Valencia, M., Estimación en modelos lineales mixtos con datos continuos usando transfor-maciones y distribuciones no normales. Tesis de Maestría. 2010.

Cevallos-Torres, Lorenzo, & Miguel Botto-Tobar. Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation. Vol. 824. Springer, 2019.

Cevallos-Torres, Lorenzo, & Miguel Botto-Tobar. "Monte carlo simulation method." Prob-lem-Based Learning: A Didactic Strategy in the Teaching of System Simulation. Springer, Cham, 2019. 87-96.

Cevallos-Torres, Lorenzo, & Miguel Botto-Tobar. "The system simulation and their learning processes." Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation. Springer, Cham, 2019. 1-11.

Cevallos-Torres, Lorenzo, & Miguel Botto-Tobar. "Case study: Project-based learning to evaluate probability distributions in medical area." Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation. Springer, Cham, 2019. 111-122.

Cevallos-Torres, Lorenzo, & Miguel Botto-Tobar. "Case study: Probabilistic estimates in the application of inventory models for perishable products in SMEs." Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation. Springer, Cham, 2019. 123-132.

Cevallos-Torres, Lorenzo, & Miguel Botto-Tobar. "Case study: Logistical behavior in the use of urban transport using the monte carlo simulation method." Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation. Springer, Cham, 2019. 97-110.

Published
2019-03-31
Stats
Abstract 195
PDF (Español (España)) 127 HTML (Español (España)) 5
How to Cite
Jurado Mero, X., Peña, J., Veloz Villon, K., & Cevallos-Torres, L. (2019). Analysis of an inventory model in perishable products applying Tabu and Montecarlo simulation metaheuristic algorithm. Ecuadorian Science Journal, 3(1), 8-14. https://doi.org/10.46480/esj.3.1.25
Section
Research Paper
Share |