Title :
Research of an Improved Genetic Algorithm for Job Shop Scheduling
Author :
Wu Jinghua ; Chen Mianzhou
Author_Institution :
Huangshi Inst. of Technol., Huangshi, China
Abstract :
Job shop scheduling is one of the most difficult NP-hard combinatorial optimize problems, in order to solve this problem, an improved Genetic Algorithm with three-dimensional coded model was put forward in this paper. In this model, the gene was coded with 3-D space, and self-adapting plot was drawn into conventional GA, then the probability of crossover and mutation can automatic adjust by fit degree. The instance shows that this algorithmic is effective to solve job shop scheduling problem.
Keywords :
computational complexity; genetic algorithms; job shop scheduling; 3D coded model; 3D space; NP-hard combinatorial optimization problem; improved genetic algorithm; job shop scheduling; self-adapting plot; Automation; Biological cells; Encoding; Equations; Genetic algorithms; Genetic mutations; Job shop scheduling; Mechatronics; Scheduling algorithm; Time measurement; Genetic Algorithm; job shop scheduling; self-adapting formatting; three-dimensional coded model;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.737
