AUTHOR=Li Xiulin , Lu Jiansha , Yang Chenxi , Wang Jiale 

TITLE=Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.909548

DOI=10.3389/fbioe.2022.909548

ISSN=2296-4185

ABSTRACT=This research studied the flexible assembly job-shop scheduling problem with lot-streaming (FAJSP-LS) which is common in multi-variety and small-batch production, such as household electrical appliances. In FAJSP-LS, an assembly stage is appended to the flexible jobshop, and jobs in the first stage are processed in a large batch to reduce switching costs while leading to more waiting time, especially in the assembly stage. This paper considered splitting the batch into a few sub-batches with unequal and consistent sizes to allow jobs to pass the two-stage system efficiently. With this objective, the problem was modeled as a mixed-integer linear program comprising two sub-problems, batch-splitting, and batch-scheduling. As the integrated problem is NP-hard, the improved bio-inspired algorithm based on artificial bee colony was proposed, including a four-layer chromosome encoding structure to describe the solution and an optimization strategy utilizing different bee colonies to solve this two-stage problem synchronously. To examine the algorithm's efficiency, a benchmark case was used to show that better solutions can be acquired with the improved algorithm whether the batch was split into equal or unequal sizes. To promote practical implementation, the algorithm was applied to a real case refrigerator workshop and showed better performance on time efficiency when jobs were split into unequal sizes compared with jobs without splitting or splitting into equal sizes.