Circuit synthesis through combination of evolutionary and swarm algorithms

Authors:
Cecília Reis;J. A. Tenreiro Machado
Affiliations:
GECAD, Knowledge Engineering and Decision Support Group, Electrical Engineering Department, Institute of Engineering of Porto, Porto, Portugal;GECAD, Knowledge Engineering and Decision Support Group, Electrical Engineering Department, Institute of Engineering of Porto, Porto, Portugal
Venue:
ICCOMP'09 Proceedings of the WSEAES 13th international conference on Computers
Year:
2009

Citing 5
Cited 0

Genetic programming: on the programming of computers by means of natural selection

Genetic programming: on the programming of computers by means of natural selection
Analysis of unconventional evolved electronics

Communications of the ACM
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Electronics: Automatic Design of Electronic Circuits and Systems by Genetic Algorithms

Evolutionary Electronics: Automatic Design of Electronic Circuits and Systems by Genetic Algorithms
The particle swarm - explosion, stability, and convergence in amultidimensional complex space

IEEE Transactions on Evolutionary Computation

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Abstract

Evolutionary Computation (EC) is a growing research field of Artificial Intelligence (AI), particularly of Computational Intelligence (CI). EC is the general term for several computational techniques which use ideas and get inspiration from natural evolution/adaptation and is divided in two main areas: the Evolutionary Algorithms (EA) and the Swarm Intelligence (SI). This paper presents hybridization between an EA algorithm - the Genetic Algorithm (GA) and a SI algorithm - the Particle Swarm Optimization Algorithm (PSO). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.