| Revista: | Polibits |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000402947 |
| ISSN: | 1870-9044 |
| Autores: | Vega Alvarado, Eduardo1 Portilla Flores, Edgar Alfredo2 Mezura Montes, Efrén3 Flores Pulido, Leticia1 Calva Yáñez, Maria Bárbara2 |
| Instituciones: | 1Universidad Autónoma de Tlaxcala, Facultad de Ciencias Básicas, Ingeniería y Tecnología, Apizaco, Tlaxcala. México 2Instituto Politécnico Nacional, Centro de Innovación y Desarrollo Tecnológico en Cómputo, México, Distrito Federal. México 3Universidad Veracruzana, Centro de Investigación en Inteligencia Artificial, Jalapa, Veracruz. México |
| Año: | 2016 |
| Periodo: | Ene-Jun |
| Número: | 53 |
| Paginación: | 83-90 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico |
| Resumen en inglés | Memetic algorithms (MA), explored in recent literature, are hybrid metaheuristics formed by the synergistic combination of a population-based global search technique with one or more local search algorithms, which in turn can be exact or stochastic methods. Different versions of MAs have been developed, and although their use was focused originally on combinatorial optimization, nowadays there are memetic developments to solve a wide selection of numerical type problems: with or without constraints, mono or multi objective, static or dynamic, among others. This paper presents the design and application of a novel memetic algorithm, MemMABC, tested in a case study for optimizing the synthesis of a four-bar mechanism that follows a specific linear trajectory. The proposed method is based on the MABC algorithm as a global searcher, with the addition of a modified Random Walk as a local searcher. MABC is a modified version of the Artificial Bee Colony algorithm, adapted to handle design constraints by implementing the feasibility rules of Deb. Four-bar mechanisms are a good example of hard optimization problems, since they are used in a wide variety of industrial applications; simulation results show a high-precision control of the proposed trajectory for the designed mechanism, thus demonstrating that MemMABC can be applied successfully as a tool for solving real-world optimization cases |
| Disciplinas: | Ciencias de la computación, Ingeniería |
| Palabras clave: | Inteligencia artificial, Ingeniería mecánica, Computación evolutiva, Algoritmos meméticos, Optimización |
| Keyword: | Computer science, Engineering, Artificial intelligence, Mechanical engineering, Evolutionary computation, Memetic algorithms, Optimization |
| Texto completo: | Texto completo (Ver PDF) |
