Kurs Code
optaprac
Dauer
21 hours (üblicherweise 3 Tage inklusive Pausen)
Überblick
In diesem Kurs wird ein praktischer Ansatz zum Unterrichten von OptaPlanner . Es stellt den Teilnehmern die Werkzeuge zur Verfügung, die zur Ausführung der Grundfunktionen dieses Werkzeugs erforderlich sind.
Machine Translated
Schulungsübersicht
Planner introduction
- What is OptaPlanner?
- What is a planning problem?
- Use Cases and examples
Bin Packaging Problem Example
- Problem statement
- Problem size
- Domain model diagram
- Main method
- Solver configuration
- Domain model implementation
- Score configuration
Travelling Salesman Problem (TSP)
- Problem statement
- Problem size
- Domain model
- Main method
- Chaining
- Solver configuration
- Domain model implementation
- Score configuration
Planner configuration
- Overview
- Solver configuration
- Model your planning problem
- Use the Solver
Score calculation
- Score terminology
- Choose a Score definition
- Calculate the Score
- Score calculation performance tricks
- Reusing the Score calculation outside the Solver
Optimization algorithms
- Search space size in the real world
- Does Planner find the optimal solution?
- Architecture overview
- Optimization algorithms overview
- Which optimization algorithms should I use?
- SolverPhase
- Scope overview
- Termination
- SolverEventListener
- Custom SolverPhase
Move and neighborhood selection
- Move and neighborhood introduction
- 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
- Local Search concepts
- Hill Climbing (Simple Local Search)
- Tabu Search
- Simulated Annealing
- Late Acceptance
- Step counting hill climbing
- Late Simulated Annealing (experimental)
- Using a custom Termination, MoveSelector, EntitySelector, ValueSelector or Acceptor
Evolutionary algorithms
- Evolutionary Strategies
- Genetic Algorithms
Hyperheuristics
Exact methods
- Brute Force
- Depth-first Search
Benchmarking and tweaking
- Finding the best Solver configuration
- Doing 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
- Short introduction to Drools
- Writing Score Function in Drools
Integration
- Overview
- Persistent storage
- SOA and ESB
- Other environment
Erfahrungsberichte
Verwandte Kategorien
Kombinierte Kurse
Sonderangebote
12/16/2019 - 09:30
Hannover
01/08/2020 - 09:30
Stuttgart
01/13/2020 - 09:30
München
01/13/2020 - 09:30
München
01/13/2020 - 09:30
Stuttgart
01/22/2020 - 09:30
Nürnberg
01/29/2020 - 09:30
Nürnberg
EINIGE UNSERER KUNDEN









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is growing fast!
We are looking to expand our presence in Germany!
As a Business Development Manager you will:
- expand business in Germany
- recruit local talent (sales, agents, trainers, consultants)
- recruit local trainers and consultants
We offer:
- Artificial Intelligence and Big Data systems to support your local operation
- high-tech automation
- continuously upgraded course catalogue and content
- good fun in international team
If you are interested in running a high-tech, high-quality training and consulting business.
Apply now!