Title :
Scheduling of Re-entrant Line Based on Swarm Intelligence
Author :
Deng, Ke ; Lin, Jie ; Wang, Feng
Author_Institution :
Coll. of Econ. & Manage., Tongji Univ., Shanghai
Abstract :
Re-entrant line is considered as one of the most complex manufacturing processes distinguished from job shop and flow shop. Based on the analysis of collective activities of ant colony, the typical example of swarm intelligence, a new model of constructing swarm intelligence on multi-agent system (SIMAS) for scheduling of re-entrant line is proposed. In this model, single ant agent is endowed with intelligence by inference engine to adapt to dynamic and complex constraints of re-entrant line. Ant colony comprised of hundreds of intelligent ant agents search optimal scheduling schemes by distributed computing mode in order to improve search efficiency. The unique queen of ant colony evaluates scheduling schemes and hereby updates pheromones, so that the single antpsilas knowledge can be shared by other ants. Also the relevant algorithm, ant colony scheduling algorithm (ACSA) is given. Finally, the validity of the model and algorithm is verified by simulation experiments.
Keywords :
computational complexity; flow shop scheduling; inference mechanisms; job shop scheduling; multi-agent systems; optimisation; production management; search problems; ant colony scheduling algorithm; flow shop scheduling; inference engine; job shop scheduling; manufacturing process; multi-agent system; reentrant line scheduling; search optimal scheduling; swarm intelligence; Distributed computing; Engines; Intelligent agent; Job shop scheduling; Manufacturing processes; Multiagent systems; Optimal scheduling; Particle swarm optimization; Processor scheduling; Scheduling algorithm; Re-entrant Line; Scheduling; Swarm Intelligence;
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
DOI :
10.1109/KAM.2008.76
