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  • Timefold Solver 1.22.1
  • Using Timefold Solver
  • Using Timefold Solver: Overview
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Timefold Solver 1.22.1

    • Introduction
    • PlanningAI Concepts
    • Getting Started
      • Overview
      • Hello World Quick Start Guide
      • Quarkus Quick Start Guide
      • Spring Boot Quick Start Guide
      • Vehicle Routing Quick Start Guide
    • Using Timefold Solver
      • Using Timefold Solver: Overview
      • Configuring Timefold Solver
      • Modeling planning problems
      • Running Timefold Solver
      • Benchmarking and tweaking
    • Constraints and Score
      • Constraints and Score: Overview
      • Score calculation
      • Understanding the score
      • Adjusting constraints at runtime
      • Load balancing and fairness
      • Performance tips and tricks
    • Optimization algorithms
      • Optimization Algorithms: Overview
      • Construction heuristics
      • Local search
      • Exhaustive search
      • Move Selector reference
    • Responding to change
    • Integration
    • Design patterns
    • FAQ
    • New and noteworthy
    • Upgrading Timefold Solver
      • Upgrading Timefold Solver: Overview
      • Upgrade to the latest version
      • Upgrade from OptaPlanner
      • Backwards compatibility
    • Enterprise Edition

Using Timefold Solver: Overview

Solving a planning problem with Timefold Solver consists of the following steps:

  1. Model your planning problem as a class annotated with the @PlanningSolution annotation, for example the Timetable class.

  2. Configure a Solver, for example a First Fit and Tabu Search solver for any Timetable instance.

  3. Load a problem data set from your data layer. That is the planning problem.

  4. Solve it with Solver.solve(problem) which returns the best solution found.

inputOutputOverview
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