Architecture
How SolverForge uses WASM and HTTP to solve constraints
Concepts
Understand the core concepts behind SolverForge
This section covers the foundational concepts you need to understand when working with SolverForge.
In This Section
- Architecture - How SolverForge uses WASM and HTTP to solve constraints
- Constraint Satisfaction - Core concepts of constraint satisfaction and optimization
Overview
SolverForge solves constraint satisfaction and optimization problems (CSPs). Given:
- A set of planning entities with planning variables to assign
- A set of constraints that define valid and preferred solutions
- An objective function (score) to optimize
The solver searches for an assignment of values to planning variables that:
- Satisfies all hard constraints (feasibility)
- Optimizes soft constraints (quality)
Example: Employee Scheduling
| Concept | Example |
|---|---|
| Planning Entity | Shift |
| Planning Variable | Shift.employee |
| Problem Fact | Employee, Skill |
| Hard Constraint | Employee must have required skill |
| Soft Constraint | Balance assignments fairly |
| Score | HardSoftScore (e.g., 0hard/-5soft) |
The solver tries different employee assignments for each shift, evaluating constraints until it finds a feasible, high-quality solution.
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