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Course Outline
Introduction to the Planner
- Understanding OptaPlanner
- Definition of a planning problem
- Use cases and illustrative examples
Bin Packing Problem Example
- Problem definition
- Problem scale
- Domain model diagram
- Main entry point
- Solver configuration
- Domain model implementation
- Score configuration
Travelling Salesman Problem (TSP)
- Problem definition
- Problem scale
- Domain model
- Main entry point
- Chaining mechanisms
- Solver configuration
- Domain model implementation
- Score configuration
Planner configuration
- Overview
- Solver configuration
- Modeling your planning problem
- Utilizing the Solver
Score calculation
- Score terminology
- Selecting a Score definition
- Calculating the Score
- Performance optimization techniques for score calculation
- Reusing score calculations outside the Solver
Optimization algorithms
- Search space size in real-world scenarios
- Does the Planner find the optimal solution?
- Architecture overview
- Overview of optimization algorithms
- Selecting the appropriate optimization algorithms
- SolverPhase
- Scope overview
- Termination criteria
- SolverEventListener
- Custom SolverPhase
Move and neighborhood selection
- Introduction to Moves and neighborhoods
- Generic Move Selectors
- Combining multiple MoveSelectors
- EntitySelector
- ValueSelector
- General Selector features
- Custom moves
Construction heuristics
- First Fit
- Best Fit
- Advanced Greedy Fit
- The Cheapest insertion
- Regret insertion
Local search
- Concepts of Local Search
- Hill Climbing (Simple Local Search)
- Tabu Search
- Simulated Annealing
- Late Acceptance
- Step counting hill climbing
- Late Simulated Annealing (experimental)
- Utilizing custom Termination, MoveSelector, EntitySelector, ValueSelector, or Acceptor
Evolutionary algorithms
- Evolutionary Strategies
- Genetic Algorithms
Hyperheuristics
Exact methods
- Brute Force
- Depth-first Search
Benchmarking and tuning
- Finding the optimal Solver configuration
- Conducting a benchmark
- Benchmark report
- Summary statistics
- Statistics per dataset (graph and CSV)
- Advanced benchmarking
Repeated planning
- Introduction to repeated planning
- Backup planning
- Continuous planning (windowed planning)
- Real-time planning (event based planning)
Drools
- Brief introduction to Drools
- Writing Score Function in Drools
Integration
- Overview
- Persistent storage
- SOA and ESB
- Other environments
21 Hours
Testimonials (1)
The training definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide. It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.
