180 citations
- Horia Hulubei National Institute for R and D in Physics and Nuclear EngineeringRO68 papers
- University of Naples Federico IIIT65 papers
- Centre National de la Recherche ScientifiqueFR64 papers
- Eötvös Loránd UniversityHU64 papers
- HUN-REN Institute for Nuclear ResearchHU64 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di NapoliIT64 papers
- Brunel University of LondonGB63 papers
- HUN-REN Wigner Research Centre for PhysicsHU63 papers
- Sapienza University of RomeIT63 papers
- Universidad Autónoma de MadridES63 papers
- University of GenoaIT63 papers
- University of Notre DameUS63 papers
22 papers · 1 filter
Evolving Evolutionary Algorithms with Patterns
Mihai Oltean
A new model for evolving Evolutionary Algorithms (EAs) is proposed in this paper. The model is based on the Multi Expression Programming (MEP) technique. Each MEP chromosome encode…
Using Traceless Genetic Programming for Solving Multiobjective Optimization Problems
Mihai Oltean, Crina Grosan
Traceless Genetic Programming (TGP) is a Genetic Programming (GP) variant that is used in cases where the focus is rather the output of the program than the program itself. The mai…
Solving even-parity problems using traceless genetic programming
Mihai Oltean
A genetic programming (GP) variant called traceless genetic programming (TGP) is proposed in this paper. TGP is a hybrid method combining a technique for building individuals and a…
Multi Expression Programming -- an in-depth description
Mihai Oltean
Multi Expression Programming (MEP) is a Genetic Programming variant that uses a linear representation of chromosomes. MEP individuals are strings of genes encoding complex computer…
Fermi level equilibration at the metal-molecule interface in plasmonic systems
Andrei Stefancu, Seunghoon Lee, Li Zhu +4
We highlight a new metal-molecule charge transfer process by tuning the Fermi energy of plasmonic silver nanoparticles (AgNPs) in-situ. The strong adsorption of halide ions upshift…
Evolving Evolutionary Algorithms using Multi Expression Programming
Mihai Oltean, Crina Groşan
Finding the optimal parameter setting (i.e. the optimal population size, the optimal mutation probability, the optimal evolutionary model etc) for an Evolutionary Algorithm (EA) is…