ELEA -- Build your own Evolutionary Algorithm in your Browser
Markus Wagner, Erik Kohlros, Gerome Quantmeyer, Timo K\"otzing

TL;DR
ELEA is a user-friendly, browser-based toolkit that enables easy assembly, execution, and analysis of evolutionary algorithms, facilitating experimentation and education with minimal setup.
Contribution
ELEA introduces an open source, drag-and-drop framework for designing and testing evolutionary algorithms directly in the browser, reducing barriers for experimentation and learning.
Findings
Easy-to-use interface accelerates algorithm experimentation
Supports export and visualization of results
Suitable for educational and exploratory purposes
Abstract
We provide an open source framework to experiment with evolutionary algorithms which we call "Experimenting and Learning toolkit for Evolutionary Algorithms (ELEA)". ELEA is browser-based and allows to assemble evolutionary algorithms using drag-and-drop, starting from a number of simple pre-designed examples, making the startup costs for employing the toolkit minimal. The designed examples can be executed and collected data can be displayed graphically. Further features include export of algorithm designs and experimental results as well as multi-threading. With the very intuitive user interface and the short time to get initial experiments going, this tool is especially suitable for explorative analyses of algorithms as well as for the use in classrooms.
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Taxonomy
TopicsEvolutionary Algorithms and Applications · Metaheuristic Optimization Algorithms Research · Advanced Multi-Objective Optimization Algorithms
