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Course Outline

Introduction to Planning

  • Understanding OptaPlanner
  • Defining a Planning Problem
  • Use Cases and Practical Examples

Case Study: Bin Packing Problem

  • Problem Statement
  • Problem Scale
  • Domain Model Diagram
  • Main Execution Method
  • Solver Configuration
  • Implementing the Domain Model
  • Configuring the Score

Case Study: Travelling Salesman Problem (TSP)

  • Problem Statement
  • Problem Scale
  • Domain Model
  • Main Execution Method
  • Chaining Techniques
  • Solver Configuration
  • Implementing the Domain Model
  • Configuring the Score

Configuring the Planner

  • Overview
  • Solver Configuration
  • Modelling Your Planning Problem
  • Utilising the Solver

Score Calculation

  • Score Terminology
  • Selecting a Score Definition
  • Calculating the Score
  • Performance Optimisation for Score Calculation
  • Reusing Score Calculation Outside the Solver

Optimization Algorithms

  • Real-World Search Space Size
  • Does Planner Guarantee an Optimal Solution?
  • Architecture Overview
  • Overview of Optimization Algorithms
  • Choosing the Right Optimization Algorithm
  • SolverPhase
  • Scope Overview
  • Termination Criteria
  • SolverEventListener
  • Custom SolverPhase

Selecting Moves and Neighbourhoods

  • Introduction to Moves and Neighbourhoods
  • Generic Move Selectors
  • Combining Multiple MoveSelectors
  • EntitySelector
  • ValueSelector
  • General Selector Features
  • Custom Moves

Construction Heuristics

  • First Fit
  • Best Fit
  • Advanced Greedy Fit
  • Lowest Cost Insertion
  • Regret Insertion

Local Search

  • Local Search Concepts
  • Hill Climbing (Simple Local Search)
  • Tabu Search
  • Simulated Annealing
  • Late Acceptance
  • Step Counting Hill Climbing
  • Late Simulated Annealing (Experimental)
  • Utilising 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 Techniques

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 Functions in Drools

Integration

  • Overview
  • Persistent Storage
  • SOA and ESB
  • Other Environments
 21 Hours

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