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 Many optimization initiatives fail—not because the math is wrong, but because the application around the model is.BI tools, dashboards, and lightweight app frameworks like Streamlit are great for reporting and visualization, but they cannot support interactive, collaborative decision-making.The AIMMS WebUI solves three critical business problems dashboards can’t: Interactive planning with real feedback from the optimization model Guided workflows for complex decision processes Secure, multi-user collaboration What Business Problem Does the AIMMS WebUI Really Solve? 1. Optimization requires interaction, not reportingDashboards show results. AIMMS shows options.Planning is iterative:change assumptions → run optimization → review trade-offs → adjust inputs → repeatIn AIMMS, users directly manipulate inputs in tables, maps, Gantt charts, and graphs, with changes propagated instantly across all dependent calculations and visualizations. Optimization runs are user-triggered Results ap

I recently interviewed several new AIMMS users.They all came from a strong Python background.They all still use Python today.And without coordinating, they told the exact same story.The learning curve? Surprisingly gentle.Their experience was consistent:Within two weeks, they had a working toy model. After that, moving into more advanced AIMMS features felt natural. WebUI, scenario handling, Math Model Inspector — all accessible quickly.In other words:If you know Python, learning AIMMS is not the hard part.That often surprises people — especially those who assume that a domain-specific optimization language must be difficult or academic.It isn’t.The real challenge starts after the honeymoon phaseAfter the first few weeks, something else happens.The excitement of “I can model this!” fades…and a more serious question emerges:“How do I structure this model so it can survive real business use?”Several users independently pointed to the same challenge:👉 Choosing the right structure for a b

Dear all,thank you very much for allowing me to be a member of this community. I am very impressed by the tool and find it very interesting.I am studying logistics. At the moment, I am writing my bachelor’s thesis about optimizing the supply chain from refineries to tank terminals using rail and inland waterways.On your website, I saw that oil companies are already using the SC Navigator tool. I have completed the online training on the fundamentals, which was very well structured and clearly explained. However, I am still wondering how I can apply this knowledge in practice.Are there any example courses or case studies for SC Navigator that show how to optimize the supply chain for oil products, for example from a refinery to tank terminals?In this context, several factors are important, such as: Are freight costs (€/ton) specified in the Cost Per UOM column? Is it possible to model a supply chain where suppliers are defined as supply nodes and warehouses or storage terminals are de

Need to securely store 'secrets' such as passwords or API keys for your application?We released a new service to cater for that. Your app secrets will be securely stored in an Azure Key Vault. Read more about it on: https://documentation.aimms.com/cloud/managing-secrets.html 

SC Navigator 26.1.1Date January 8, 2026 New Features Transport Navigator has been extended with the ability to allow flexibility in the delivery day for each customer, through the attribute Pattern Group. This flexibility can be used to balance the warehouse effort through the attributes Minimum Relative Capacity and Maximum Relative Capacity. See Getting Started with Transport Navigator for details. Improvements A new Source Location Weight attribute has been added to the Locations sheet to extend the Maximum # of Source Locations constraint by allowing weighted source contributions. For more details, see the documentation Optimization Parameters and Constraints. On the COG Settings page, a counter has been added to the Fixed Location selector. In Transport Navigator, the readability of the main text on the Solve in Background dialog page is improved by adjusting the font color, which was previously too light and hard to read. In Transport Navigator, the titles

 When you need to control an AIMMS model from an external environment, the Python-Bridge provides a robust interface. Specifically, the aimmspy module allows Python scripts to connect to a running AIMMS session to exchange data and trigger logic. Key Capabilities of aimmspyThe aimmspy module enables your Python environment to interact with the AIMMS model through the following actions: Data Exchange: Read and write values for AIMMS sets, parameters, and variables directly from Python data structures. Procedure Execution: Call AIMMS procedures from your script to run optimizations or data processing tasks. Session Management: Establish and manage the connection between the Python interpreter and the AIMMS project.  What the Guide CoversThe article walks through a foundational "Hello World" scenario to establish the connection. Key steps include: Installing the Module: Setting up aimmspy within your Python environment. Connecting to AIMMS: Identifying the correct project and establ

Each time a user runs an AIMMS app, a unique process ID is generated. I need to include this ID when exporting a data file containing multiple parameters, so that users can link each exported file to its corresponding run.Could you advise on how to programmatically access this ID within AIMMS? Additionally, is it possible to test this functionality in our local development environment, or is it only supported when connected to the AIMMS PRO environment?There is a similar topic: Reading the Jobs screen data from the PRO server into an AIMMS project. | AIMMS Community  However, I don’t quite understand how it works, as my goal is to retrieve the unique ID for each run, not just a list of jobs. If a user runs the app several times in quick succession, how can we differentiate these runs?Thanks for the help.