Research on Batch Scheduling Technology for Hybrid Flow Shop with Skip Ability Based on Improved Genetic Algorithm

Batch scheduling and dispatching in the hybrid flow shop production mode is an inevitable development trend, as it effectively improves low resource utilization and reduces excessive work-in-process inventory. This study proposes a multi-objective batch scheduling technique for the hybrid flow shop based on the concept of batch flow. It establishes a multi-objective optimization model with the sub-batch as the smallest processing unit and utilizes an improved genetic algorithm to enhance search capability, resolving the optimization issues of work-in-process inventory and delivery time in the hybrid flow shop. The approach is further developed and analyzed using actual data from a specific workshop, demonstrating its effectiveness in enhancing production efficiency and reducing work-in-process inventory. The results validate the feasibility and efficacy of the proposed algorithm.