What's the shortest trip to visit all European capitals? Or the cheapest vehicle routing schedule to restock all our retail stores? How do we optimize our cloud machines? When do we assign nurses to shifts in our hospitals to make them as happy as possible? Which crops do we plant on which fields for the optimal revenue? What's the fairest tennis club schedule? Which algorithms work well and scale out on these kind of planning problems? Certainly not Brute Force or other exhaustive heuristics!

In this session, we will: - Introduce constraint satisfaction optimization

Demo a few use cases

Use weighted hard and soft constraints to formalize business goals

Walk through a bit of example code in Java of the open source constraint satisfaction solver OptaPlanner (www.optaplanner.org [1])

Explain how continuous planning or real-time planning works

Deal with scalability challenges by using heuristics and metaheuristics (such as Tabu Search and Simulated Annealing).

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