Cloud-based estimation of marine freight rates

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The logistics chain is crucial for manufacturing, accounting for 20% of final product costs. Currently, tools are slow due to the numerous variables. A software-based solution is developed training a Neural Network to estimate freight costs, using historical data from VGSC and market information.

Start date: 01/11/2015

Duration in months: 18

Problem Description

The logistics chain is an important part of the manufacturing process. Logistics can account for 20% of the final cost of a product for a manufacturing company, and in cases where products need to be shipped by sea, this can rise to 90%. Therefore, finding an optimal transport choice is fundamental.

Goals

New services

Challenges

A software solution must be developed, which takes into account all possible variables in the determination of the optimal transport choice in timeframes compatible with the fast decision-making required by the process.

Innovation results

A software-based solution has been developed to estimate freight costs for specific shipments using VGSC's historical data and market information. The solution uses a Neural Network (NN) and is delivered as a secure SaaS, with performance improving with more data.

Business impact

IMATIA launched a freight cost estimation service, combining data processing, information analysis, and NN knowledge. VGSC tested the SaaS platform, gaining knowledge on freight rate influences from historical data. CESGA developed a HPC Python toolkit for hyper-parametric search on TensorFlow.

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