Title :
A dynamic schedule methodology for discrete job shop problem based on Ant Colony Optimization
Author :
Meilin, Wang ; Xiangwei, Zhang ; Qingyun, Dai ; Jinbin, He
Author_Institution :
Fac. of Inf. Eng., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
Job shop scheduling is an important problem in implementing Manufacturing Execution System (MES). In this paper, an algorithm based on Ant Colony Optimization (ACO) is proposed to solve a discrete job shop scheduling problem (DJSSP). A dynamic schedule methodology is applied to DJSSP. The main concept is that the real-time production status from the MES IDT (Intelligent Data Terminal) is passed to the pheromone updating rule to guide the transfer of the work pieces. MES IDE is a hardware platform deployed in the shop floor with the aim of real-time and wireless manufacturing. This methodology has been put into real-life practice in several manufacturing enterprises according to its universality. It has achieved excellent efficiency in terms of real-time scheduling and planning, JIT (Just-In-Time) manufacturing etc.
Keywords :
cooperative systems; job shop scheduling; just-in-time; optimisation; ant colony optimization; discrete job shop scheduling problem; dynamic schedule methodology; intelligent data terminal; just-in-time manufacturing; manufacturing execution system; realtime scheduling; Algorithm design and analysis; Ant colony optimization; Convergence; Dynamic scheduling; Hardware; Job shop scheduling; Manufacturing; Processor scheduling; Production; Scheduling algorithm; ACO; Discrete; Job Shop Scheduling; MES;
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
DOI :
10.1109/ICIME.2010.5477648
