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A Cloud-Based Transport Management System Automates Daily Planning of Thousands of Orders

Logistics and Transportation
Microsoft Azure
.NET
C#
Angular

Description

Brief results of the collaboration:

  • The solution maximizes vehicle load (100–120%) and assigns properly equipped vehicles for temperature-sensitive, fragile, inflammable, and other cargos.
  • With the platform, the operators’ efforts can be reduced by 70%.
  • Used by around 100 logistics companies, the system facilitates the delivery of up to 1,000 orders per day by each service provider.

The customer

Founded in 1999, the company is an Oslo-based provider of software for logistics and transportation. The customer’s portfolio features a cloud-based transport management system, as well as a range of mobile apps for drivers, operators at logistics centers, warehouse workers, etc.

The need

Initially, the customer partnered with Altoros to develop a mobile app that would improve communication between operators at logistics centers and drivers in the field, as well as automate order placement, invoicing, etc. Satisfied with the cooperation, the customer decided to rely on our expertise in migrating its transport management system (TMS) to the cloud.

The company already had a legacy desktop TMS, but it was monolith and difficult to maintain and support. With limited functionality, it mainly allowed for placing orders and checking their status. To attract new customers and improve the offering, it was decided to develop a new cloud-based TMS and significantly extend its functionality. For instance, the customer wanted to enable smart planning to maximize the load of a car fleet.

The challenges

Under the project, the team at Altoros had to address the following issues:

  • While building optimal workflows, it was necessary to take into account the specifics of the logistics processes. The module had to ensure maximum vehicle load, correlate cargo volume with vehicle capacity, and account for a cargo type (temperature-sensitive, fragile, inflammable, etc.).
  • The solution needed to track the vehicle location in real time.
  • For smooth migration, the new cloud-based system had to be synched with the legacy desktop system.

The solution

Building the solution as a set of microservices allowed engineers at Altoros to enable high scalability, as well as ease of maintenance and support. Being still under development, Azure Service Fabric—a platform for deploying microservices—had some integration issues with Visual Studio Team Services. So, our team has delivered a number of workarounds to fix this.

Working on the planning module, experts at Altoros developed a number of algorithms that automatically assigned a vehicle for a particular cargo, maximized the vehicle load, and split an order between different cars if needed.

To enable real-time tracking by operators, our developers built an API and integrated it with an app on the driver’s smartphone to track geolocation and send data to the system.

To facilitate migration, our developers utilized Azure Functions, enabling real- time synchronization between the developed and legacy systems. Using Azure Service Bus, it was possible to enhance throughput capacity and scalability of the new solution.

To ensure security, engineers at Altoros implemented certificate-based authentication, which granted access to the system only on submitting a dynamic private key—each time different for a different user.

The outcome

The customer has successfully launched the TMS to around 100 logistics companies across Norway. Built as a set of microservices, the delivered solution enables improved customization and scalability. The synchronization with the legacy system helped to smoothly migrate to the cloud. Automating dozens of thousands of orders daily, the developed system also reduced the operators’ efforts by 70%.

Technology stack

Platform

Microsoft Azure

Programming languages

.NET Framework (C#), TypeScript

Frameworks and tools

Azure Service Fabric, Azure Functions, Azure Service Bus, Visual Studio Team Services, AngularJS, Elastic Stack, Zabbix

Database

Microsoft SQL Server, CosmosDB (DocumentDB)

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