Genetic Quantum Algorithms with Binary Observation

New evolutionary algorithms based on quantum computing models are presented. Qubits are used to encode a potential solution. In the evolution of solutions, the quantum gates are used instead of traditional genetic crossover and mutation operators. Through binary observation of a quantum (qubit) representation, binary chromosomes are generated and processed, which are used in a classical genetic algorithm. Pseudocodes of quantum genetic algorithms with observation and modification procedures are given. Quantum genetic operators of rotation (interference), mutation (inversion) and crossover are considered. A comparison of traditional and quantum genetic algorithms has been made. The advantages and disadvantages of the above models and their areas of application are noted.