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Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 29-631
Full Name: Cecilia Reis
Position: Professor
Age: ON
Sex: Female
Address: Rua Dr. Antonio Bernardino de Almeida, 431
Country: PORTUGAL
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E-mail address: cmr@isep.ipp.pt
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Title of the Paper: Crossing Genetic and Swarm Intelligence Algorithms to Generate Logic Circuits
Authors as they appear in the Paper: Cecilia Reis and J. A. Tenreiro Machado
Email addresses of all the authors: cmr@isep.ipp.pt,jtm@isep.ipp.pt
Number of paper pages: 10
Abstract: Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust.!
This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). 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.
Keywords: Artificial intelligence, Computational intelligence, Evolutionary computation, Genetic algorithms, Particle swarm optimization, Digital circuits
EXTENSION of the file: .pdf
Special (Invited) Session: Circuit Synthesis through Combination of Evolutionary and Swarm Algorithms
Organizer of the Session: 620-198
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