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Release Notes

Overview

Release Notes for Core Release 7.5.2

We are excited to announce the release of version 7.5.2 of our JOpt Core Library. This version introduces significant improvements, new features, and optimizations that enhance stability, performance, and user experience. Below is a detailed overview of what's new.

Before You Start

To help you integrate our JOpt library effectively, please visit:

If you are developing a REST application, check out our updated OpenAPI schema for better client generation support.

Major Changes and Achievements

Integration of LLMs (Large Language Models)

JOpt has always utilized machine learning and intelligent algorithms at its core. Over the past year, we have made substantial improvements in terms of stability, user experience, and AI-driven enhancements. We are also actively developing LLM integrations with JOpt to provide better support and accelerate development.

Join Our Closed Beta Program
We are currently running a closed beta program for our LLM-powered features. If you are interested, please reach out to us.

Find example training questions here.

Updated REST API Specification

Generating a REST client based on a complex schema can be challenging. To improve the experience, we now provide two different schema definitions, starting from JOpt TourOptimizer schema version 1.3.0-SNAPSHOT:

  1. Full Schema

    • Includes the original stricter definition with additional "oneOf" keys.
    • Generated with Springdoc 2.8.4.
    • Download Full Schema.
    • Works with the latest Java OpenAPI Generator (7.11.0) as a Maven dependency.

  2. Cleaned Schema

    • Same as the full schema but without "oneOf" keys.
    • Download Cleaned Schema.
    • Works with the latest @openapitools/openapi-generator-cli (v2.16.3) for Angular.
    • Works with the latest Docker image openapitools/openapi-generator-cli (v7.11.0) for C# and Python.

New Core Library Features

This release introduces three powerful new features to improve optimization efficiency and flexibility.

1. Optimization Solution Comparison Tool

Our most sophisticated feature this year.

The Optimization Solution Comparison Tool allows users to modify an existing optimization result and compare it with an adjusted version. This is particularly useful in real-world optimization scenarios, where customers may prefer different routing decisions due to visual preferences or business constraints.

  • Why is this useful?
    • Customers often expect routes to follow a direct geographical path, but the optimizer may select a more optimal route that considers time windows, constraints, and restrictions.
    • This tool allows for comparing the original optimizer result with a modified version (e.g., changing visit orders of nodes).
    • The tool generates a comparison report, showing the impact on costs, violations, and performance.

Read more about this feature in our docs. Further, get an example.

2. Performance Mode (Faster Optimization)

We introduce Performance Mode, an optional setting that allows optimizations to run up to 50% faster.

  • How does it work?

    • Reduces the number of concurrent solutions during genetic evolution.
    • Disables certain optimization operators that increase computational overhead.
    • Ideal for large-scale problems with fewer constraints (e.g., long working hours and fewer restrictions).

  • When to use it?

    • When speed is a priority over absolute precision.
    • When the optimization does not require highly constrained solutions.
    • Suitable for fleet optimizations with flexible schedules.

Enable it with this property:

props.setProperty("JOpt.PerformanceMode", "true");

Read more about Performance Mode in our docs. Further, get an example.

3. Zone Crossing Penalty

In many real-world scenarios, crossing between different zones (e.g., via bridges or tunnels) should be minimized due to time delays and additional costs.

  • The Zone Crossing Penalty feature allows users to assign a cost penalty when a resource crosses a defined zone boundary.

  • This ensures that crossings only occur when absolutely necessary, making the routes more practical and cost-effective.

  • How does it work?

    • The optimizer applies an additional cost multiplier whenever a vehicle crosses a zone.
    • This ensures that crossings only happen at the beginning and end of a shift, reducing unnecessary back-and-forth travel.

Enable it with this property:

props.setProperty("JOpt.Clustering.PenlalizeZoneCodeCrossing", true);
props.setProperty("JOpt.Clustering.PenlalizeZoneCodeCrossingMultiplier", "3.0");

Read more about the Zone Crossing Penalty in our docs. Further, get an example.

Improvements

  • Core Library Bug Fixes: Numerous bugs have been addressed in our core library. A detailed changelog is available here.

  • Demo Angular Application Update: The demo application (source) at demo.dna-evolutions.com has been updated to the latest version of Angular (19.1).

  • JOpt.TourOptimizer and Other Updates: Our JOpt.TourOptimizer (link on GitHub) has been updated to the latest version of Spring, along with many other dependencies. In addition, we fixed some schema problems.

Overview of updated REST Clients with examples:

Of course you can create your own client in the language of your choice utilizing our OpenAPI description for JOpt TourOptimizer here.

Previous Releases

Release Notes for Core Release 7.5.1

We are excited to announce the release of version 7.5.1 of our core library. This version marks a significant transition and introduces new features, enhancements, and bug fixes. Here's what's new:

Before you start: Please visit our Java example repository to learn how you can integrate our JOpt library natively in your Java application or visit one of our REST client example repositories if you are planning a REST application in a language of your choice.

Major Changes

  • Java Version Upgrade: Our core library has been moved from Java 8 to Java 17. This will be the last version to include a Java 8 compatible version along with a corresponding legacy dll version. Future updates will require users who are still on Java 8 or prefer to use dll to switch to our JOpt.TourOptimizer, which is a Spring Application with a Swagger interface. This allows for building clients in a desired language and version.

New Additions

Python Example Client: We've added a new example client in Python for JOpt.TourOptimizer, providing more flexibility and accessibility for Python developers. Please contact us for more information, as using the client requires some personal instructions ([email protected]).

New Core Library Features:

Improvements

  • Core Library Bug Fixes: Numerous bugs have been addressed in our core library. A detailed changelog is available here.

  • Demo Angular Application Update: The demo application (source) at demo.dna-evolutions.com has been updated to the latest version of Angular. A new feature allows users to drag and drop a fixed number of nodes and resources on a map for optimization.

  • JOpt.TourOptimizer and Other Updates: Our JOpt.TourOptimizer (link on GitHub) has been updated to the latest version of Spring, along with many other dependencies. We've also introduced our latest TypeScript REST-Client.

  • REST-Client Examples Update: We've updated our REST-client examples for Java, C# and Angular to serve as a starting point for our customers. These can be found on GitHub. Further, we added a new Python client.

**Overview REST Clients with examples: **

Of course you can create your own client in the language of your choice utilizing our OpenAPI description for JOpt TourOptimizer here.

General Notes

  • We've made many other minor improvements and optimizations across our platform to enhance performance and user experience.

As always, we are committed to providing high-quality and up-to-date software solutions. We encourage our users to migrate to the newer versions to take full advantage of the latest features and improvements.

For a complete list of changes, please refer to the CHANGELOG.md.