A Block-Guided Artificial Bee Colony Algorithm for Distributed Assembly Flowshop Scheduling with Sequence-Dependent Setup Times

Abstract The Distributed Assembly Permutation Flowshop Scheduling Problem with Sequence-Dependent Setup Times (DAPFSP-SDST) arises in many modern manufacturing supply chains. This paper proposes a Block-Guided Artificial Bee Colony (BG-ABC) algorithm for this problem with the aim of minimizing the makespan. An idle-aware block compression mechanism is developed to lock adjacent product pairs with minimal setup time and zero assembly idle time into atomic blocks, reducing the search space for global exploration. To further enhance search adaptability, a Sliding Window Upper Confidence Bound 1 (SW-UCB1) scheme is embedded in the employed bee phase to dynamically select neighborhood operators based on their recent performance. In the onlooker bee phase, local search is restricted to the Critical Job Subsequence so that computational effort is concentrated on the bottleneck region of the schedule. Moreover, a refinement-and-reconstruction mechanism is proposed in the scout bee phase to counteract the stagnation risk induced by block compression. Finally, extensive experiments on benchmark instances demonstrate that BG-ABC significantly outperforms state-of-the-art algorithms, verifying its effectiveness in solving DAPFSP-SDST.