New Hexaly integration, Q&A with Seeker creator, observability for decision science, and more
Welcome back! We’re currently at INFORMS Annual 2024 in Seattle and we’ll fill you in on our takeaways soon. In the meantime, here’s what we’ve been up to…
We went to the Gurobi Decision Intelligence Summit in Las Vegas and had a great time meeting folks applying OR across all sorts of fascinating use cases. (Did you know a planning optimization model is used to produce nearly a third of the world’s dairy exports?) We were excited that our presentation on the value of DecisionOps resonated strongly with both practitioners and business leaders.?
What’s new?
New integration: Bring your Hexaly decision model to Nextmv?
Solve optimization problems with Hexaly? The Nextmv Hexaly integration provides a new way to efficiently run, test, and manage Hexaly decision models with Nextmv’s DecisionOps tools and infrastructure.? Read more
Operationalizing Python decision models: configurable options, simple I/O, custom logging, and more
If you’re building decision models in Python, our Python SDK and decision science platform make the development process faster (and easier) so you can get your model safely into production. Read more?
Create webhooks for your model
Simplify integrations with tools like Slack for signaling the status of your runs. Define the webhooks and review the conversations, requests, and responses in your terminal or the Nextmv UI. Read more
Pyomo + SCIP + Nextmv
Quickly configure SCIP as the solver for your Pyomo model within Nextmv: it’s a one-line code change. Start with a community app, customize your model, and deploy directly to Nextmv from your Python environment. Read more
Thought pieces
How to scale logistics planning with optimization models
What if you could explore 100s or 1,000s of possible plans in seconds instead of 10s of plans in days or weeks? Optimization models make this possible all while keeping humans in the loop to ensure quality and build trust. Read more
领英推荐
Observability & decision science: Monitoring optimization model performance and more
When decision models power real-life operations, any sort of model performance failure is a nightmare. Learn why observability in the operations research space is often a challenge – and how to give your team more visibility into model performance with DecisionOps. Read more
Community highlight
The Optimization Challenge
We are proud to support The Practical Optimization Sprint, a 5-day sprint hosted by Cristina Radu, Borja Menéndez, and Carlos Zetina filled with activities focused on applying OR in practice. Sign up to get updates.? Learn more
Events
2024 INFORMS Annual Meeting | Seattle, WA | October 20 -23, 2024
On-demand viewing
Uncertainty, ML + OR, and stochastic optimization: Demo and Q&A with Seeker creator
What approaches are available to decision scientists and operations researchers to incorporate more randomness and uncertainty into their models? We explore this, ML + OR, and stochastic optimization with Nextmv and Seeker. Watch now
Bring your custom Python decision model to Nextmv and accelerate time to value
If you develop decision models in Python, this presentation will save you time (and the added effort of building and maintaining DecisionOps tools). Accelerate development of your optimization models with features for testing, deploying, managing, and collaborating. Watch now
Until next time!
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Founder & CEO at Hexaly
4 个月I am so glad ?? not to say proud that Hexaly is now fully integrated and seamlessly available inside the great Nextmv platform for #DecisionOps. Thank you,?Nextmv,?for the great work, and thank you for your trust. We're delighted to work with all of you and your customers to make mathematical optimization easier, faster, and more scalable! Hexaly combines primal and dual methods into a global optimization solver. Its modeling API is nonlinear and set-oriented. It also supports black-box optimization, making Simulation+Optimization or ML+Optimization straightforward. It can be viewed as a super extension of both MINLP and CP paradigms. No other solver in the market supports such a modeling API, which is available in Python, Java, C#, and C++. As a result, Hexaly is the fastest, most scalable, flexible, and robust solver for Routing, Picking, Scheduling, Packing, Clustering, Assignment, Matching, Location, and many more, especially in Supply Chain and Workforce optimization. This is why Hexaly is used in production by Amazon, FedEx, Procter & Gamble, Starbucks, Bosch, Sony, Airbus, Air Liquide, TotalEnergies, EDF, Renault, Softbank, Veolia, and many others worldwide. Check the benchmarks here: https://www.hexaly.com/benchmarks
Maps | OS | Cloud | Web | Software
4 个月nice!