A.I. constraint optimization with OptaPlanner
summary
Open-source Java solver OptaPlanner solves vehicle routing, rostering and scheduling by encoding hard vs soft constraints, incremental scoring and local-search heuristics. Benchmarks report 5–15% faster routes on academic Belgium sets (customers see 15–30% reductions in driving time), an example app uses real road data and supports real-time re-routing with pinned stops, and rostering runs yield ~53% improvement in employee well‑being metrics. Implementation options: Drools rules, incremental Java or constraint streams; it works and scales.
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chapters (11)
- 0:00Start
- 4:12Road are asymmetric
- 6:27What is constraint solving?
- 17:00What is a planning problem?
- 30:05Calling the solve method
- 38:45Required skill constraint (Java)
- 43:41Required skill constraint (DRL)
- 45:21Who's in control?
- 46:24Conference scheduling
- 47:28Getting started
- 47:54Build from source
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