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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JS7 JobScheduler
JS7 JobScheduler is an Open Source workload automation system designed for performance, resilience and security. It provides unlimited performance for parallel execution of jobs and workflows. JS7 offers cross-platform job execution, managed file transfer, complex no-code job dependencies and a real REST API.
Platforms
- Cloud scheduling from Containers for Docker®, Kubernetes®, OpenShift® etc.
- True multi-platform scheduling on premises for Windows®, Linux®, AIX®, Solaris®, macOS® etc.
- Hybrid use for cloud and on premises
User Interface
- Modern, no-code GUI for inventory management, monitoring and control with web browsers
- Near real-time information brings immediate visibility of status changes and log output of jobs and workflows
- Multi-client capability, role based access management
High Availability
- Redundancy and Resilience based on asynchronous design and autonomous Agents
- Clustering for all JS7 products, automatic fail-over and manual switch-over
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statsmodels
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.
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