JOpt.TourOptimizer
JOpt.TourOptimizer is an enterprise route optimization and scheduling engine for logistics, dispatch, transportation, and field service operations. It solves VRP, CVRP, VRPTW, pickup and delivery, multi-depot planning, heterogeneous fleet routing, and workforce scheduling under real-world business constraints.
The platform supports time windows, working hours, capacities, skills and expertise levels, territories, zone governance, overnight stays, alternate destinations, and custom business rules. Available as a Java SDK and Docker-based REST API with OpenAPI/Swagger, JOpt.TourOptimizer integrates into existing software platforms.
It helps organizations improve planning efficiency, service quality, transparency, SLA compliance, and operational reliability at scale. It is designed for software vendors, enterprise developers, and operations teams that need scalable optimization technology for production use, not just basic route calculation.
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Google Cloud Run
Cloud Run is a fully-managed compute platform that lets you run your code in a container directly on top of Google's scalable infrastructure. We’ve intentionally designed Cloud Run to make developers more productive - you get to focus on writing your code, using your favorite language, and Cloud Run takes care of operating your service.
Fully managed compute platform for deploying and scaling containerized applications quickly and securely. Write code your way using your favorite languages (Go, Python, Java, Ruby, Node.js, and more). Abstract away all infrastructure management for a simple developer experience. Build applications in your favorite language, with your favorite dependencies and tools, and deploy them in seconds. Cloud Run abstracts away all infrastructure management by automatically scaling up and down from zero almost instantaneously—depending on traffic. Cloud Run only charges you for the exact resources you use. Cloud Run makes app development & deployment simpler.
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Dask
Dask is open source and freely available. It is developed in coordination with other community projects like NumPy, pandas, and scikit-learn. Dask uses existing Python APIs and data structures to make it easy to switch between NumPy, pandas, scikit-learn to their Dask-powered equivalents. Dask's schedulers scale to thousand-node clusters and its algorithms have been tested on some of the largest supercomputers in the world. But you don't need a massive cluster to get started. Dask ships with schedulers designed for use on personal machines. Many people use Dask today to scale computations on their laptop, using multiple cores for computation and their disk for excess storage. Dask exposes lower-level APIs letting you build custom systems for in-house applications. This helps open source leaders parallelize their own packages and helps business leaders scale custom business logic.
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