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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DXcharts
DXcharts is a white-label financial charting library. With 1-day integration, impressive native mobile apps, and an optional data feed, Devexperts has created a charting solution that sets new standards in performance.
Freedom to choose with 4 tailored options:
- Free white-label open source charting library (DXcharts Lite)
- DXcharts financial charting library: a white-label charting library with trading functionality
- DXcharts widget: a quick and easy tool for websites and blogs
- DXcharts source code for full ownership of the product
Why choose DXcharts?
- Fully customizable to match your brand: adjust colors, fonts, icons, and layouts effortlessly
- Access over 100 indicators, 48 drawing tools, and features like trading and news monitoring—all within the chart
- Designed for all devices with seamless mobile-friendly compatibility
- Explore DXcharts with a free trial
- Delivered ready with dxFeed, but you can also integrate any other market data source
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ggplot2
ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behavior of existing functions, and if we do make changes to existing behavior we will do them for compelling reasons. If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages.
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