Title :
Quantum-inspired genetic algorithms
Author :
Narayanan, Ajit ; Moore, Mark
Author_Institution :
Dept. of Comput. Sci., Exeter Univ., UK
Abstract :
A novel evolutionary computing method-quantum inspired genetic algorithms-is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient evolutionary computing methods. The basic terminology of quantum mechanics is introduced before a comparison is made between a classical genetic algorithm and a quantum inspired method for the travelling salesperson problem. It is informally shown that the quantum inspired genetic algorithm performs better than the classical counterpart for a small domain. The paper concludes with some speculative comments concerning the relationship between quantum inspired genetic algorithms and various complexity classes
Keywords :
computational complexity; genetic algorithms; quantum theory; travelling salesman problems; complexity classes; evolutionary computing; genetic algorithm; performance; quantum inspired genetic algorithms; quantum mechanics; terminology; travelling salesperson problem; Computational modeling; Computer science; Electrons; Energy states; Genetic algorithms; Orbits; Quantum computing; Quantum mechanics; Vectors; Wave functions;
Conference_Titel :
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2902-3
DOI :
10.1109/ICEC.1996.542334