Research on Dynamic Multi-objective FJSP Based on Genetic Algorithm
| Autor: | Bin-feng Jin, Bi Li |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
021103 operations research Job shop scheduling Computer science 0211 other engineering and technologies 02 engineering and technology Dynamic priority scheduling Scheduling (computing) Genetic algorithm Simulated annealing 0202 electrical engineering electronic engineering information engineering Task analysis 020201 artificial intelligence & image processing Time point Global optimization |
| Zdroj: | DASC/PiCom/DataCom/CyberSciTech |
| DOI: | 10.1109/dasc/picom/datacom/cyberscitec.2018.00-97 |
| Popis: | This paper mainly research on a rescheduling strategy and a new hybrid genetic algorithm are presented for the insertion of new processing task in the workshop scheduling and the precocity problems existing in the application of genetic algorithm. Firstly, the time interval is set according to the time point of the new task, and the optimization of multi-objective scheduling is guaranteed. Then by improving the genetic algorithm and combining simulated annealing algorithm, a new hybrid algorithm is presented and implements optimization processing in flexible shop scheduling. The experiment shows that the algorithm improves the global optimization ability. Finally, the simulation results show that the algorithm can obtain a higher quality Pareto solution when static scheduling and insertion of new task. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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