Introducing modularity and homology in grammatical evolution to address the analog electronic circuit design problem
We present a new approach based on grammatical evolution (GE) aimed at addressing the analog electronic circuit design problem. In the new approach, called multi-grammatical evolution (MGE), a chromosome is a variable-length codon string that is divided into as many partitions as subproblems result...
| Autores: | , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2020 |
| País: | España |
| Recursos: | Universidad Nacional de Educación a Distancia |
| Repositório: | e-spacio. Repositorio Institucional de la UNED |
| Idioma: | inglês |
| OAI Identifier: | oai:e-spacio.uned.es:20.500.14468/22399 |
| Acesso em linha: | https://hdl.handle.net/20.500.14468/22399 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Genetic programming grammatical evolution evolutionary electronics analog circuit automatic design |
| Resumo: | We present a new approach based on grammatical evolution (GE) aimed at addressing the analog electronic circuit design problem. In the new approach, called multi-grammatical evolution (MGE), a chromosome is a variable-length codon string that is divided into as many partitions as subproblems result from breaking down the original optimization problem: circuit topology and component sizing in our case. This leads to a modular approach where the solution of each subproblem is encoded and evolved in a partition of the chromosome. Additionally, each partition is decoded according to a specific grammar and the final solution to the original problem emerges as an aggregation result associated with the decoding process of the different partitions. Modularity facilitates the encoding and evolution of the solution in each subproblem. On the other way, homology helps to reduce the potentially destructive effect associated with standard crossover operators normally used in GE-based approaches. Seven analog circuit designs are addressed by an MGE-based method and the obtained results are compared to those obtained by different methods based on GE and other evolutionary paradigms. A simple parsimony mechanism was also introduced to ensure compliance with design specifications and reduce the number of components of the circuits obtained. We can conclude that our method obtains competitive results in the seven circuits analyzed. |
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