1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
To successfully apply evolutionary algorithms to the solution of increasingly complex problems, we must develop effective techniques for evolving solutions in the form of interact...
We present a novel means of algorithmically describing a growth process that is an extension of Lindenmayer’s Map L-systems. This growth process relies upon a set of rewrite rule...
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
We propose a hybrid algorithm (called ALPINE) between Genetic Algorithm and Dantzig's Simplex method to approximate optimal solutions for the Flexible Job-Shop Problem. Local...