Abstract
The flexible flow shop (FFS) is defined as a multistage flow shop with multiple parallel machines. FFS scheduling problem is a complex combinatorial problem which has been intensively studied in many real world industries. In the FFS scheduling problem, each job has to be processed on any machine at each stage, but it is not considered that how the jobs are transported from one machine to another. In this study, materials are transported from one machine to another through autonomous guided vehicles (AGV) system. In this paper, we propose a genetic algorithm (GA) for solving FFS scheduling problem in which AGVs are used to transport materials. We design effective coding and decoding scheme and genetic operators including crossover and mutation. The effectiveness of the algorithm is verified by simulation experiments.
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