6533b872fe1ef96bd12d30c8
RESEARCH PRODUCT
An evolutionary approach to multi-objective scheduling of mixed model assembly lines
Giovanni PerroneV. GrassoGiovanni CelanoSergio FicheraU. La Commaresubject
Mixed modelMutation operatorEngineeringMixed Model assembly line; Multiobjective scheduling; Genetic algorithmFitness functionMixed Model assembly lineGeneral Computer Sciencebusiness.industryCrossoverGeneral EngineeringGenetic algorithmMultiobjective schedulingStop timeControl parametersAssembly linebusinessAlgorithmSmoothingdescription
In this paper a multi-objective genetic algorithm for the scheduling of a mixed model assembly line is proposed, pursuing the line stop time minimisation together with the component usage smoothing. Specific features of the developed GA are step by step random selection of diversified crossover and mutation operators, population control for the substitution of duplicate chromosomes, and in-process updating of GA control parameters. Three different formulation of the fitness function were been tested with some distinct line configurations.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 1999-10-01 |