OptaPlanner is an open-source, lightweight, embeddable planning engine. With this, organizations can reduce costs, improve service quality, fulfill employee wishes, and reduce carbon emissions. 

It is object oriented programming and functional programming friendly and, according to the company, it works to allow programmers to efficiently solve optimization problems.

This open-source tool improves plans and schedules with hard constraints and soft constraints which apply to plain domain objects and can call existing code. 

OptaPlanner also supports continuous planning to publish the schedule weekly, three days before execution; non-disruptive replanning for changes to a published schedule; real-time planning to react quickly on disruptions, overconstrained planning for when there are not enough resources to cover work; and pinning so the user is still in control of their schedule.

It combines artificial intelligence optimization algorithms such as Tabu Search, Simulated Annealing, Late Acceptance, and other metaheuristics, with score calculation and other constraint solving techniques for NP-complete or NP-hard problems.

OptaPlanner works directly with Java, Kotlin, Scala, and Python; integrates with both Quarkas and Spring boot; and runs on Kubernetes and Openshift as well as all major clouds.

Lastly, the Red Hat build of OptaPlanner is now included in Red Hat Applications Foundations. This allows users to build scalable planning applications that work to solve complex optimization challenges.

These challenges include rostering, vehicle routing, scheduling, or many other constraint satisfaction problems.

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