Agent-Based Modeling and Simulation of Inventory Disruption Management in Supply Chain
Inventory management system is a complex network of worldwide components that produce, handle, and distribute specific products. Due to the complex interaction between the decisions of such components, system performance analysis under various conditions is necessary. Such environment calls for appr...
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Published in | 2018 International Conference on High Performance Computing & Simulation (HPCS) pp. 1008 - 1014 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.07.2018
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Subjects | |
Online Access | Get full text |
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Summary: | Inventory management system is a complex network of worldwide components that produce, handle, and distribute specific products. Due to the complex interaction between the decisions of such components, system performance analysis under various conditions is necessary. Such environment calls for appropriate modeling and simulation tools that help to construct an artificial environment to assess the dynamic system. Agent-based technology has been proven as a suitable approach for modeling such complex networks with distributed actors to ensure high performance of the simulation run. The performance can be measured through various key performance indicators in terms of logistics aspects (customer satisfaction, number of missed orders, number of late orders, total tardiness) and financial aspects (overall profit). This paper illustrates the utility of agent-based modeling to evaluate the overall impact of disruptions on system performance in order to support decision makers in handling inventory disruptions. Such model can be useful to prevent and react against the effects of disruption events on system performance. As an illustrative case, agent-based simulation models of distribution chain that buys and distributes final products are introduced. Inventory system's behavior, as well as the effects of mitigating strategies during disruption situation, are studied. |
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ISBN: | 1538678780 9781538678787 |
DOI: | 10.1109/HPCS.2018.00158 |