Title :
A modified continuous genetic algorithm and its application for job-shop scheduling
Author :
Xijin, Guo ; Li, Gao
Author_Institution :
Coll. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
Abstract :
The continuous genetic algorithm has a risk for long staying on one stage before it gains the best solution. This paper presents the modified continuous genetic algorithm to overcome this disadvantage. This algorithm is applied to job-shop scheduling to test its validity. The test results show this algorithm is good at operation and convergence.
Keywords :
convergence; genetic algorithms; production control; GA; job-shop scheduling; modified continuous genetic algorithm; Automation; Educational institutions; Genetic algorithms; Intelligent control; Scheduling algorithm; Testing;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1021493
