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commit 6232a6d7a41bdea835769258160841d2fcd05b87
Author: rikkola <[email protected]>
AuthorDate: Tue Apr 29 17:27:51 2025 +0300

    Migrate optaplanner.org to kie-website #1936
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-id: drools_old_downloads
-title: Old Downloads
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-
-# Old Downloads
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-# Optaplanner
+# Solve planning and scheduling problems with OptaPlanner
 
-This section is work-in-progress. Please refer to 
[Documentation](https://kie.apache.org/docs/documentation/) for the latest 
documentation.
\ No newline at end of file
+A fast, easy-to-use, open source AI constraint solver for software developers
+
+# What can OptaPlanner do?
+
+OptaPlanner optimizes plans and schedules with *hard constraints* and *soft 
constraints*.
+It **reduces costs** substantially, improves **service quality**, **fulfills 
employee wishes** and **lowers carbon emissions**.
+
+
+- Vehicle routing
+  - Quick router for a fleet of vehicles.
+- Employee rostering
+  - Assign shifts to employees by skills and availability.
+- Maintenance scheduling
+  - Timely upkeep of machinery and equipment.
+- Conference scheduling
+  - Schedule speakers and talks by availability and topic.
+- School timetabling
+  - Compact schedules for teachers and students.
+- Task assigment
+  - Assign tasks by priority, skills and affinity.
+- Cloud optimization
+  - Bin packaging and defragmentation of cloud resources.
+- Job shop scheduling
+  - Reduce makespan for assembly lines.
+
+# What is OptaPlanner?
+
+OptaPlanner is a Open Source Java™ AI constraint solver to optimize conference 
schedules.
+
+OptaPlanner is a lightweight, embeddable planning engine. It enables everyday 
Java™ programmers to solve optimization problems efficiently. It is also 
compatible with other JVM languages (such as Kotlin and Scala). Constraints 
apply on plain domain objects and can call existing code. There’s no need to 
input constraints as mathematical equations. Under the hood, OptaPlanner 
combines sophisticated Artificial Intelligence optimization algorithms (such as 
Tabu Search, Simulated Annealing, L [...]
+
+OptaPlanner is open source software, released under the Apache License. It is 
written in 100% pure Java™, runs on any JVM and is available also in the Maven 
Central repository.
+
+
+# Modern mathematical optimization
+OptaPlanner is a lightweight, embeddable planning engine. It enables everyday 
programmers to solve optimization problems efficiently. Constraints apply on 
plain domain objects and can call existing code. It is Object Oriented 
Programming (OOP) and Functional Programming (FP) friendly. There’s no need to 
input constraints as mathematical equations.
+OptaPlanner supports 
+- **Continuous planning** to weekly publish the schedule, 3 weeks before 
execution 
+- **Non-disruptive replanning** for changes to an already published schedule 
+- **Real-time planning** to react on real-time disruptions in the plan within 
milliseconds 
+- **Overconstrained planning** when there are too few resources to cover all 
the work 
+- **Pinning** so the user is still in control over the schedule
+
+Under the hood, OptaPlanner combines sophisticated Artificial Intelligence 
optimization algorithms (such as Tabu Search, Simulated Annealing, Late 
Acceptance and other metaheuristics) with very efficient score calculation and 
other state-of-the-art constraint solving techniques for NP-complete or NP-hard 
problems.
+
+# Compatibility
+
+Compatibility
+OptaPlanner works directly from:
+- Java 
+- Kotlin 
+- Scala 
+- Python (experimental)
+
+OptaPlanner integrates seamlessly with:
+
+- Quarkus 
+- Spring Boot
+
+OptaPlanner runs on:
+
+- Kubernetes and OpenShift 
+- All major clouds
+
+OptaPlanner is open source software, released under the Apache License.
+
+# Code example
+To optimize a problem from Java™ code, add the <code>optaplanner-core</code> 
jar and call <code>Solver.solve()</code>:
+
+```
+    SolverFactory<MyRoster> factory = SolverFactory.create(...);
+  
+    // My domain specific class as input
+    MyRoster problem = ...;
+
+    Solver<MyRoster> solver = factory.buildSolver();
+    // My domain specific class as output
+    MyRoster solution = solver.solve(problem);
+
+    for (MyShift shift : solution.getShifts()) {
+       // Each shift is now assigned to an employee
+       assertNotNull(shift.getEmployee());
+    }
+```


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