A decision support system for internal logistics operations management

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Abstract
Continuous improvement in industrial processes has made efficient internal material transportation critical. This study presents a decision support system for tracking internal transportation vehicles and providing effective inner logistics management. The proposed model includes a barcoding based transportation vehicle tracking system, a forecasting model for daily transportation demands of different buildings and presents a predictive demand-vehicle assignment mathematical model. Results show that the model reduces the operational costs due to vehicle search and vehicle transportation, and material damage costs due to vehicle-material mismatch at a great extent.

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