Dynamic parts scheduling in multiple job shop cells considering intercell moves and flexible routes

Aiming at the problem of scheduling with flexible processing routes and exceptional parts that need to visit machines located in multiple job shop cells, a pheromone based approach (PBA) using multi-agent is presented in this paper, in which various types of pheromone inspired by ant colony optimization (ACO) are adopted as the basis of negotiation among agents. By removing redundant routes and constructing coalition agents, communication cost and negotiation complexity are reduced, and more importantly, the global performance of scheduling is improved. The performance of the PBA is evaluated via experiments with respect to the mean flow time, maximum completion time, mean tardiness, ratio of tardy parts, and ratio of intercell moves. Computational results show that compared with various heuristics, the PBA has significant advantages with respect to the performance measures considered in this paper.