DocumentCode
1635144
Title
Quantum-inspired genetic algorithms
Author
Narayanan, Ajit ; Moore, Mark
Author_Institution
Dept. of Comput. Sci., Exeter Univ., UK
fYear
1996
Firstpage
61
Lastpage
66
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location
Nagoya
Print_ISBN
0-7803-2902-3
Type
conf
DOI
10.1109/ICEC.1996.542334
Filename
542334
Link To Document