Genetic Algorithm for Single Machine Scheduling Problem with Setup Times
| Autor: | Quan Ouyang, Hong Yun Xu |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Mathematical optimization
education.field_of_study Mutation operator Single-machine scheduling Computer science Offspring Population-based incremental learning Population Crossover Scheduling (production processes) General Medicine Genetic operator Scheduling (computing) Chromosome (genetic algorithm) Genetic algorithm ComputingMethodologies_GENERAL education Premature convergence |
| Zdroj: | Applied Mechanics and Materials. :1678-1681 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.457-458.1678 |
| Popis: | This paper describes a genetic algorithm to solve the single machine scheduling problem with setup times, which uses the fixed two point crossover operator (F2PX) to produce new offspring chromosomes and uses the roulette wheel method in the selection of the chromosome population. In order to avoid the premature convergence we use a neighborhood based mutation operator to conduct disturbance in our genetic algorithm. Through the application of this genetic algorithm in practical scheduling problems, the effect of the genetic algorithm proposed in this paper is remarkable. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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