González-Reséndiz, J.; Arredondo-Soto, K.C.; Realyvásquez-Vargas, A.; Híjar-Rivera, H.; Carrillo-Gutiérrez, T. Integrating Simulation-Based Optimization for Lean Logistics: A Case Study. Appl. Sci.2018, 8, 2448.
González-Reséndiz, J.; Arredondo-Soto, K.C.; Realyvásquez-Vargas, A.; Híjar-Rivera, H.; Carrillo-Gutiérrez, T. Integrating Simulation-Based Optimization for Lean Logistics: A Case Study. Appl. Sci. 2018, 8, 2448.
González-Reséndiz, J.; Arredondo-Soto, K.C.; Realyvásquez-Vargas, A.; Híjar-Rivera, H.; Carrillo-Gutiérrez, T. Integrating Simulation-Based Optimization for Lean Logistics: A Case Study. Appl. Sci.2018, 8, 2448.
González-Reséndiz, J.; Arredondo-Soto, K.C.; Realyvásquez-Vargas, A.; Híjar-Rivera, H.; Carrillo-Gutiérrez, T. Integrating Simulation-Based Optimization for Lean Logistics: A Case Study. Appl. Sci. 2018, 8, 2448.
Abstract
The present work aims at the comprehensive application of stochastic and optimization tools with the support of Information and Communication Technologies (ICT) through a case study in a logistics process for electronic goods; simulation and Response Surface Methodology (RSM) are applied for this purpose. The problem to be evaluated is to define an optimal distribution cost for products shipped to wholesale customers located in different cities in Mexico from a manufacturing plant in Tijuana, Mexico. The factors under study are the product allocation for each distribution center, finished good inventory level and on time deliveries, which are supposed to be significant to get the objective. The methodology applied for this problem considers the design of a discrete event simulation model to represent virtually the real life of logistics process, which is considered a complex system due to different activities are interrelated to carry it out. This model is used to execute the different experiments proposed by the RSM. The results obtained from simulation model were analyzed with the RSM to define the mathematical model that allows identifying the parameters of the factors in order to optimize the process. The findings prove how the ICT facilitate the application of stochastic tools with the purpose of process optimization.
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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