About
About SolverForge
Constraint solving for planning, scheduling, routing, and allocation applications in Rust.
Core Capabilities
SolverForge is Rust-native optimization infrastructure for real planning systems. Build domain models in Rust, express hard and soft constraints as code, and integrate solving into scheduling, dispatch, allocation, and operational planning systems.
Rust Solver Core
A production-ready constraint solver with Constraint Streams, zero-allocation move types, score analysis, and a stable Rust API.
Employee Scheduling Tutorial
Work through shifts, skills, preferences, and solver-driven updates end to end.
solverforge-ui
Frontend components and integration helpers for scheduling-heavy products built on SolverForge.
solverforge-maps
Routing primitives, cached road-network data, and travel metrics for map-backed planning and dispatch systems.
How It Works
SolverForge applications start with planning solutions and entities represented as ordinary Rust structs. Constraint Streams define what must be satisfied and what should be optimized, while score analysis helps explain tradeoffs. The solver searches for better solutions and emits progress, best-solution, and finished events that application code can consume.
solverforge-ui and solverforge-maps extend that core into interactive
scheduling and routing applications.
Common Uses
- Workforce scheduling with hard compliance rules and soft preferences
- Routing and dispatch with travel-time-aware scoring
- Interactive planning applications that need solver feedback in the UI
Open Source by Design
SolverForge ships as open source Rust crates, examples, and documentation on GitHub. Teams can audit the solver, study the reference implementations, and extend it for their own domains.
Designed for Operational Complexity
SolverForge is suited to scheduling, routing, capacity planning, assignment, and similar problems where feasibility and business value depend on many interacting rules.