Evolutionary neural architecture search (ENAS) has recently received increasing attention by effectively finding high-quality architectures, which however consumes high computational cost training the encoded each individual for complete epochs in evaluation. Numerous ENAS approaches have been developed to reduce evaluation cost, but it is often difficult most of these achieve accuracy. To addr...

Evolutionary approaches to molecular docking typically hybridize with local search methods, more specifically, the Solis-Wet method. However, some studies indicated that local search methods might not be very helpful in the context of molecular docking. An evolutionary algorithm with proper genetic operators can perform equally well or even outperform hybrid evolutionary approaches. We show tha...

In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...

For the calibration of laser induced plasma spectrometers robust and eecient local search methods are required. Therefore, several local optimizers from nonlinear optimization, random search and evolutionary computation are compared. It is shown that evolutionary algorithms are superior with respect to reliability and eeciency. To enhance the local search of an evolutionary algorithm a new meth...