Follow this step-by-step tutorial to go from a forecasted demand to optimized routes for delivery and similar use cases. Create and customize decision apps using OR-Tools, HiGHS, Pyomo, and more.
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Deploy your custom decision model from a Python environment
How to bring custom Hexaly models to Nextmv
How to add your custom Python decision model to Nextmv
Stochastic optimization with Seeker: Solving an integrated sushi production problem
Uncertainty, ML + OR, and stochastic optimization: Demo and Q&A with Seeker creator
Scenario testing for decision models: Simulate scenarios to answer "what if" questions
Bring your custom Python decision model to Nextmv: Build, test, deploy
Operationalizing HiGHS-based MIP models and Q&A with project developers
How to model continuous depot visits for vehicle routing problem (VRP)
Model multiple pickups before a dropoff for vehicle routing problem (VRP)
Vehicle activation penalties to encourage vehicle efficiency (vehicle routing, VRP)
Combining machine learning (ML) and operations research (OR) through horizontal computing
OR-Tools, VROOM & Nextplot: Open source vehicle routing and visualization
Optimization modeling with AMPL, Streamlit, and Nextmv
Link and test logistics models for demand forecasting, shift scheduling, and vehicle routing
Getting started with DecisionOps for decision science models using Gurobi
Deploy and run custom decision model
Decision model acceptance test
Operationalizing Java-based OR-Tools decision models
Q&A on CI/CD for decision science with Nicole Misek (VP of Engineering)
Nextmv AMPL integration demo
Nextmv Gurobi integration demo
Demo: Java support for the Nextmv OR-Tools integration
Switchback (A/B) testing for decision optimization models