Title :
The improvement and optimization of Job Shop Scheduling Problem based on Genetic Algorithm
Author :
Zhengcheng, Wang ; Shuang, Zhou
Author_Institution :
Economic & Manage. Dept., ZheJiang Sci-Tech Univ., Hangzhou, China
Abstract :
This paper analyzes the mathematical model of Job Shop Scheduling Problem and improves traditional Genetic Algorithms by simplifying coding,optimizing crossover and mutation operator, and introduces selection operator with sifting strategy. The simulation results show that the global search ability is greatly better than that of traditional method. The improved Genetic Algorithms can solve Job Shop Scheduling Problem effectively.
Keywords :
genetic algorithms; job shop scheduling; genetic algorithm; job shop scheduling; optimization; Genetic Algorithm; Job Shop Scheduling Problem; Sifting Strategy;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622133
