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Course Outline

Introduction to the Planner

  • Understanding OptaPlanner
  • Defining a planning problem
  • Practical use cases and examples

Example: Bin Packaging Problem

  • Problem definition
  • Scale of the problem
  • Domain model diagram
  • Main execution method
  • Solver setup
  • Implementing the domain model
  • Configuring score constraints

Travelling Salesman Problem (TSP)

  • Problem definition
  • Scale of the problem
  • Domain model structure
  • Main execution method
  • Chaining techniques
  • Solver setup
  • Implementing the domain model
  • Configuring score constraints

Configuring the Planner

  • Configuration overview
  • Solver configuration details
  • Modeling the planning problem
  • Utilizing the Solver

Calculating Scores

  • Key score terminology
  • Selecting an appropriate score definition
  • Performing score calculations
  • Performance optimization techniques for score calculation
  • Reusing score calculation logic outside the Solver

Optimization Algorithms

  • Real-world search space dimensions
  • Achieving optimal solutions with Planner
  • Architectural overview
  • Survey of optimization algorithms
  • Selecting the right optimization algorithms
  • Understanding SolverPhase
  • Concept of scope
  • Termination conditions
  • Utilizing SolverEventListener
  • Creating custom SolverPhase logic

Selecting Moves and Neighborhoods

  • Introduction to moves and neighborhoods
  • Generic Move Selectors
  • Combining multiple MoveSelectors
  • EntitySelector usage
  • ValueSelector usage
  • Advanced Selector features
  • Implementing custom moves

Construction Heuristics

  • First Fit strategy
  • Best Fit strategy
  • Advanced Greedy Fit
  • Cheapest insertion method
  • Regret insertion method

Local Search Techniques

  • Core concepts of Local Search
  • Hill Climbing (Simple Local Search)
  • Tabu Search
  • Simulated Annealing
  • Late Acceptance
  • Step counting hill climbing
  • Late Simulated Annealing (experimental)
  • Implementing custom Termination, MoveSelector, EntitySelector, ValueSelector, or Acceptor

Evolutionary Algorithms

  • Evolutionary Strategies
  • Genetic Algorithms

Hyperheuristics

Exact Methods

  • Brute Force approach
  • Depth-first Search

Benchmarking and Tuning

  • Identifying the optimal Solver configuration
  • Conducting benchmarks
  • Interpreting benchmark reports
  • Analyzing summary statistics
  • Dataset-specific statistics (graph and CSV)
  • Advanced benchmarking techniques

Repeated Planning

  • Introduction to repeated planning
  • Backup planning strategies
  • Continuous planning (windowed planning)
  • Real-time planning (event-based planning)

Drools Integration

  • Brief introduction to Drools
  • Writing Score Functions using Drools

System Integration

  • Integration overview
  • Managing persistent storage
  • Integration with SOA and ESB
  • Deploying in other environments
 21 Hours

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