Joint Scheduling for Multi-load AGVs and Parallel Production Lines Considering Bernoulli Machines

With the development of modern manufacturing, the scheduling problem of multi-load AGVs and parallel machines (MAGVPM) is gradually becoming an important issue in the field of production optimization. Parallel machines represent a generalized concept in manufacturing environments, where component processing typically involves multiple stages corresponding to distinct machines. This study proposes a novel scheduling problem integrating multi-load AGVs with parallel production lines, which falls within the scope of MAGVPM scheduling problems. To address the interdependencies between serial production lines and AGV logistics systems, a holistic production scheduling model consisting of transportation and processing tasks was formulated. For the serial line featuring Bernoulli machines and capacity-limited buffers, Markov method enables precise computation of job processing times. An enhanced tabu search algorithm that incorporates genetic operators to generate feasible solutions is implemented. The effectiveness of the improved tabu algorithm was proved through computational experiments.