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Control System Synthesis by Means of Cartesian Genetic Programming
Balandina G.I.
implementation use point mutation to form new mathematical expressions. Steady-state genetic algorithm is chosen
The Parallel Genetic Algorithm for Construction of Technological Objects Neural Network Models
Tynchenko, Vadim Sergeevich, Petrovsky, Eduard Arkadievich, Tynchenko, Valeriya Valerievna
The parallel genetic algorithms implementation for neural networks models construction is discussed
The problem of the genetic algorithm initial configuration selection
N, A Timofeev, P, V Peresunko, S, R Nekhonoshin, V, V Kukartsev, V, V Tynchenko, A, S Mikhalev
The genetic algorithm is one of the most well-known and frequently used global optimization
Hyper-heuristics for structure and parameters tuning in evolutionary algorithms
Pupkov A. a Sopov E. a b Panfilov I. a b Samarin V. a Telesheva N. a Kuzmich R.
Hyper-heuristics for structure and parameters tuning in evolutionary algorithms
Optimization Algorithm for IPTV Video Service Delivery over SDN Using MEC Technology
Manariyo S., Khakimov A., Pyatkina D., Muthanna A.
are looking for new ways to efficiently deliver video content to specific customers or classes of customers
Spectral Decomposition of Mappings of Molecular Genetic Information in the System Basis of Single Nucleotide Functions
Stepanyan I., Lednev M.
This paper presents and visualizes examples of large amounts of genetic information using a new
The problem of the genetic algorithm initial configuration selection
N, A Timofeev, P, V Peresunko, S, R Nekhonoshin, V, V Kukartsev, V, V Tynchenko, A, S Mikhalev
The problem of the genetic algorithm initial configuration selection
Design of grid systems to solve complex industrial engineering problems
Tynchenko, Valeriya Valerievna, Solovyov, Evgeniy Alekseevich, Tynchenko, Sergei Vasilyevich
in the process of decision making is proposed the using of the multiobjective genetic algorithm. In the study
Optimal Trajectories Synthesis of a Mobile Robots Group Using Cartesian Genetic Programming
Diveev A., Balandina G.
is solved. The proposed algorithm uses numerical approach from the class of symbolic regression methods
Genetic algorithm of network graph multi-objective optimization as an instrument of project monitoring
Prokopyev O.
remains a vital part of modern project management, defining prospects of successful implementation

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