This paper considers the use of multi-objective genetic algorithms for solving a typical production chain problem, in which two consecutive production stages have to schedule their internal work while taking into account each other’s requirements. We focus on a multi-objective genetic algorithm recently proposed in the related literature, i.e. IGA (Intelligent Genetic Algorithm), comparing the solutions it yields with those obtained by two state-of-the-art genetic optimizers. A set of preliminary computational tests on the mentioned case study using industrial data indicate that IGA is a promising multi objective optimizer for typical supply chain planning and scheduling problems
Ciavotta, M., Dotoli, M., Fanti, M., Hammadi, S., Koubaa, S., Meloni, C. (2006). Genetic algorithms for the setup coordination in consecutive stages of a production chain. In International Workshop on Logistics & Transportation (pp.218-223).
Genetic algorithms for the setup coordination in consecutive stages of a production chain
Ciavotta, M;
2006
Abstract
This paper considers the use of multi-objective genetic algorithms for solving a typical production chain problem, in which two consecutive production stages have to schedule their internal work while taking into account each other’s requirements. We focus on a multi-objective genetic algorithm recently proposed in the related literature, i.e. IGA (Intelligent Genetic Algorithm), comparing the solutions it yields with those obtained by two state-of-the-art genetic optimizers. A set of preliminary computational tests on the mentioned case study using industrial data indicate that IGA is a promising multi objective optimizer for typical supply chain planning and scheduling problemsFile | Dimensione | Formato | |
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