Title :
Combining CA and PSO to solve flexible job shop scheduling problem
Author :
Wei Zhou ; Yan-ping Bu ; Ye-qing Zhou
Author_Institution :
Sch. of Bus., East China Univ. of Sci. & Technol., Shanghai, China
fDate :
May 31 2014-June 2 2014
Abstract :
The flexible job shop scheduling problem (FJSP) is an extension of the classic job shop scheduling problem (JSP), which breaks through the uniqueness of limit resources, allows a procedure in many machines processing and one machine processing many kinds of different types of procedures. It is more practical and complex than JSP. The computational complexity of FJSP is much higher, which disables exact solution methods and makes heuristic approaches more qualified. A hybrid optimization algorithm, CPSO, based on the cultural algorithm and particle swarm optimization algorithm, is proposed in this paper to solve the FJSP. The objective is to minimize makespan. Computational results show that this hybrid method is able to solve efficiently these kinds of problems.
Keywords :
computational complexity; job shop scheduling; minimisation; particle swarm optimisation; CA; CPSO; FJSP; computational complexity; cultural algorithm; flexible job shop scheduling problem; hybrid optimization algorithm; limit resources; makespan minimization; particle swarm optimization algorithm; Decision support systems; cultural algorithm; flexible job shop scheduling problem; makespan; particle swarm optimization algorithm;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852316