Version 33 (modified by abeham, 10 years ago) (diff) |
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About
Information on the team of developers, contributors, and awards that HeuristicLab has received.
Developer Resources
HeuristicLab is continously improved and extended. Here you will find helpful resources in setting up your development environment, read articles on the architecture of HeuristicLab and keep in touch with the official development roadmap.
Video Tutorials
Video tutorials show how to use the HeuristicLab environment to complete tasks such as experiment analysis, algorithm prototyping or solving regression problems.
Basic Tutorials
Advanced Tutorials
- How to create custom algorithms
- How to create user-defined problems
- How to use HeuristicLab Hive
- Rapid prototyping using the scripting environment
Application-specific Tutorials
Howtos
Howtos are detailed instructions that show how to work with HeuristicLab such as designing new problems in the GUI and how to extend HeuristicLab with new features that can be added in new plugins.
Working with HeuristicLab
- Tutorial slides: Algorithm and experiment design
- Define custom problems in the GUI
- Optimize AnyLogic simulation models
- Optimize external applications
- Experiment calculation with HeuristicLab Hive
- Use Hive engine for fine-grained parallel algorithms
- Run HeuristicLab on Linux
Extending HeuristicLab
Please also visit the Development Center for quick guides and background on the HeuristicLab architecture if you want to explore these Howtos in more depth.
- Tutorial slides: HeuristicLab programming basics
- Tutorial slides: HeuristicLab programming algorithms and problems
- Implement custom views
- Implement a basic algorithm
- Implement custom problems
- Implement GP problems
- Implement a new VRP encoding
- Implement a new VRP evaluator
- Implement a new VRP problem instance
- Integrate HeuristicLab in other applications
Additional Infrastructure
Reference
HeuristicLab includes many algorithms, problems, and operators. Here several of these are explained in more detail.
Algorithms
- Genetic algorithm
- Evolution strategy
- Offspring selection genetic algorithm
- Particle swarm optimization
- Robust taboo search
Problems
- Artificial ant problem
- External evaluation problem
- Real-valued test functions
- Traveling salesman problem
- Vehicle routing problem