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Assessment System For A Large Container Management and Optimization Problem
In logistics systems of medium and large enterprises, operators must analyze hundreds of thousands of variables to find potential improvements. This task becomes very complex in large scenarios and the taken decisions are generally based just on local changes, without regarding global factors. In this work, we present a system for the analysis and optimization of a container transport system considering variations in demand over time and global conditions. We propose a coupled empty-full container reposition model that describes liners operations in a year. We also implement an assisted process that helps users to find and estimate missing data in order to describe a complete scenario. This system allows users to make predictions and risk analysis more accurately in a short time at the same time they can obtain an optimum benefits.