Abstract
HeuristicLab is a graphical user interface (GUI) based framework for heuristic and evolutionary algorithms, designed for ease of use. It offers a plugin-based architecture (which enables users to add custom extensions without knowing the whole of the source code), a domain-independent model to represent arbitrary search algorithms, support for graphical user interfaces, and the ability to accommodate parallel algorithms. A comfortable and feature-rich graphical user interface reduces the learning effort and enables users without programming skills to use and apply HeuristicLab. Several well-known heuristic algorithms and optimization problems are already implemented in HeuristicLab and can be used off-the-shelf. Users can create and reuse plugins to integrate new features and extend the functionality of HeuristicLab. HeuristicLab supports parallel execution of algorithms on multi-core and cluster systems. It provides interactive charts for quickly and thoroughly analyzing results.
| Original language | American English |
|---|---|
| Pages (from-to) | 215-218 |
| Number of pages | 4 |
| Journal | Genetic Programming and Evolvable Machines |
| Volume | 15 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Jan 2014 |
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Hardware and Architecture
- Computer Science Applications
Fingerprint
Dive into the research topics of 'Software review: The HeuristicLab framework'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver