Title :
A new pheromone design in ACS for solving JSP
Author :
Xiao-Ian Zhuo ; Jun Zhang ; Wei-Neng Chen
Author_Institution :
SUN Yat-sen Univ., Guangzhou
Abstract :
Job shop scheduling problem (JSP) is one of the most difficult NP-hard combinatorial optimization problems due to the "combination explosion" effect. This paper presents the implementation of ant colony system on JSP by proposing a novel combination of path-construction and pheromone-representation. Based on the simple traditional path-construction, a kind of more effective pheromone is employed to improve the optimization performance. Numerical experiment is executed on several benchmark JSP cases, and yields favorable results compared with results obtained by traditional implementation of ACS for JSP.
Keywords :
combinatorial mathematics; computational complexity; job shop scheduling; optimisation; NP-hard; ant colony system; combination explosion effect; combinatorial optimization; job shop scheduling; path-construction; pheromone design; pheromone-representation; Evolutionary computation; Ant colony system; job-shop scheduling problem;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
DOI :
10.1109/CEC.2007.4424714
