Panel Furniture Production Scheduling with Limited Storage Spaces

Job shop scheduling technologies have significantly improved the production processes of panel furnitures by shortening the production cycles, leading to enlarged profit margin of enterprises. The existing job shop approaches for panel furniture production assume unlimited storage spaces between production processes, but this is not practically the case and thus limiting the efficiency of these approaches for real-world applications. This paper presents a panel furniture job shop scheduling approach with storage space constraints between processes fully considered. In particular, the scheduling is implemented using a Genetic Algorithm (GA), and the impact of the storage space limitation is encoded in the fitness function. The effectiveness of the proposed method without considering the space limit was evaluated by a comparative study in reference to the approaches reported in the literature, and the added capacity of handling limited storage spaces was further validated by an extra scenario. The experimental results show the competitiveness of the proposed approach in panel furniture production and thus it is promising for scaled up real-world applications.