In this paper, an algorithm inspired from quantum evolution and particle swarm to evolve combinational logic circuits is presented. This algorithm uses the framework of the local version of particle swarm optimization with quantum evolutionary algorithms, and integer encoding. A multi-objective fitness function is used to evolve the combinational logic circuits in order obtain feasible circuits with minimal number of gates in the design. A comparative study indicates the superior performance of the hybrid quantum evolution-particle swarm inspired algorithm over the particle swarm and other evolutionary algorithms (such as genetic algorithms) independently.
P. W. Moore and G. K. Venayagamoorthy, "Evolving Combinational Logic Circuits Using a Hybrid Quantum Evolution and Particle Swarm Inspired Algorithm," Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware (EH'05), Institute of Electrical and Electronics Engineers (IEEE), Jan 2005.
The definitive version is available at https://doi.org/10.1109/EH.2005.28
2005 NASA/DoD Conference on Evolvable Hardware (EH'05)
Electrical and Computer Engineering
Keywords and Phrases
Combinational Circuits; Combinational Logic Circuit Evolution; Evolutionary Computation; Genetic Algorithm; Hybrid Quantum Evolution; Integer Encoding; Logic Design; Logic Gates; Multiobjective Fitness Function; Particle Swarm Inspired Algorithm; Particle Swarm Optimization; Quantum Computing; Quantum Evolutionary Algorithm
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.