Combining genetic and particle swarm algorithms for the design of combinational circuits
Evolutionary computation (EC) is a growing research field of Artificial Intelligence (AI) and is divided in two main areas: the Evolutionary Algorithms (EA) and the Swarm Intelligence (SI). This paper presents an algorithm that combines an EA algorithm - the Genetic Algorithm (GA) with a SI algorith...
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| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2019
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| Texto completo: | http://hdl.handle.net/10400.22/13362 |
| País: | Portugal |
| Oai: | oai:recipp.ipp.pt:10400.22/13362 |
| Resumo: | Evolutionary computation (EC) is a growing research field of Artificial Intelligence (AI) and is divided in two main areas: the Evolutionary Algorithms (EA) and the Swarm Intelligence (SI). This paper presents an algorithm that combines an EA algorithm - the Genetic Algorithm (GA) with a SI algorithm - the Particle Swarm Optimization Algorithm (PSO). The new 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. |
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