A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling
Identical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the availability of the resources, following some allocation rule. In this work, the...
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2006
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/22620 |
| Aporte de: |
| Sumario: | Identical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the availability of the resources, following some allocation rule. In this work, the minimization of some objectives related to the due dates such as the maximum tardiness (Tmax) and the average tardiness (Tavg) were dealt with centralized and decentralized evolutive algorithms (EAs). In order to test our algorithms we used standard benchmarks. The main goal of this research was determinate the quality of the results obtained with a centralized GA and three decentralized GAs used to solve parallel machines scheduling problems. The results were compared using the ANOVA statistic method. |
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