Mathematical Modeling and Hybrid GA Optimization for Multifactory Production–Assembly Flexible Job Shop Scheduling With Adaptive Neighborhood Search

In response to the multifactory collaborative distributed characteristics of building material equipment during the manufacturing process, this paper studies the two‐stage (production–assembly) distributed assembly flexible job shop scheduling problem (DAFJSP) and constructs a corresponding mathematical model. To address this complex NP‐hard problem, a hybrid genetic algorithm with variable neighborhood search (HGA‐VNS) is proposed. The algorithm integrates multiple crossover and mutation strategies, thereby significantly enhancing global search capabilities. Concurrently, the implementation of four neighborhood operations has been demonstrated to enhance local search efficiency. To validate the effectiveness and superiority of the proposed algorithm, comparative experiments with other scheduling algorithms were conducted. The findings indicate that the proposed algorithm demonstrates notable advantages in addressing the DAFJSP.