Abstract

Allocating jobs to the best factories and scheduling them are two important problems in distributed flexible manufacturing systems that are among NP-hard problems. Many different intelligent algorithms have been proposed for these problems. In this paper, two new algorithms were proposed for distributed flexible manufacturing system (DFMS-MPN and DFMS-PPN algorithms), in which one of them was based on Memetic algorithm and the other was based on the particle swarm optimization method. In the proposed method, the distributed flexible manufacturing system was modeled by Timed Petri net and then a scheduled task was programmed by Memetic algorithm and particle swarm optimization method. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

Key words: Distributed flexible manufacturing system, scheduling, Memetic algorithm, particle swarm optimization, timed Petri net.