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Simulation as Tool for Logistic Chain Optimization

Simulation as Tool for Logistic Chain Optimization AbstractSimulation is one of the methods in which a real system is substituted with a computer model where experiments are practiced and then subsequently analyzed and evaluated. After the application of the results of simulation and verification of its effects the results are applied in the real system with the aim to optimize processes. It seems that simulation is appropriate tool which offers all useful information about how model system works in given conditions. Simulation in planning and optimizing allows better and faster understanding of processes and guarantees that operational devices will work at the top of their effectiveness. Simulation plays an important role in optimization of logistic chains organization. There is a need to analyze strictly, find narrow places, remove them and consequently to repeat simulation with the new data. It is also very profitable to parallelly simulate more possible alternatives when there is a change in input data and consequently to compare them. The model of logistic chain created by simulation will considerably influence right decisions in process solving related to distribution. Subsequent optimization of logistic chain management can be aimed at the organization where the sum of final costs for transport and warehousing is minimum in compliance with basic parameters of customers’ service level.In the paper classic systems of the management of logistic chains are compared, namely direct distribution and indirect distribution made by technology Cross-Dock canter. Final comparative analysis of both systems simulation points out not only to their advantages and disadvantages but also to the possibilities of their optimization and application in particular operational conditions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transport technic and technology de Gruyter

Simulation as Tool for Logistic Chain Optimization

Transport technic and technology , Volume 18 (2): 6 – Dec 1, 2022

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References (18)

Publisher
de Gruyter
Copyright
© 2022 Vladimír Klapita, published by Sciendo
eISSN
2585-8084
DOI
10.2478/ttt-2022-0006
Publisher site
See Article on Publisher Site

Abstract

AbstractSimulation is one of the methods in which a real system is substituted with a computer model where experiments are practiced and then subsequently analyzed and evaluated. After the application of the results of simulation and verification of its effects the results are applied in the real system with the aim to optimize processes. It seems that simulation is appropriate tool which offers all useful information about how model system works in given conditions. Simulation in planning and optimizing allows better and faster understanding of processes and guarantees that operational devices will work at the top of their effectiveness. Simulation plays an important role in optimization of logistic chains organization. There is a need to analyze strictly, find narrow places, remove them and consequently to repeat simulation with the new data. It is also very profitable to parallelly simulate more possible alternatives when there is a change in input data and consequently to compare them. The model of logistic chain created by simulation will considerably influence right decisions in process solving related to distribution. Subsequent optimization of logistic chain management can be aimed at the organization where the sum of final costs for transport and warehousing is minimum in compliance with basic parameters of customers’ service level.In the paper classic systems of the management of logistic chains are compared, namely direct distribution and indirect distribution made by technology Cross-Dock canter. Final comparative analysis of both systems simulation points out not only to their advantages and disadvantages but also to the possibilities of their optimization and application in particular operational conditions.

Journal

Transport technic and technologyde Gruyter

Published: Dec 1, 2022

Keywords: Logistic chain; simulation of process; distribution; transportation chain; Cross-Dock technology

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