Evolutionary multi-objective optimization of spiking neural networks for solving classification problems is studied in this paper. By means of a Paretobased multi-objective geneti...
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Evolutionary Algorithms (EA) that can be used in realistic risky scenarios. The path returned by the a...
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
This work analyses two heuristic algorithms based on the genetic evolution theory applied to direct sequence code division multiple access (DS/CDMA) communication systems. For diff...