Dual Resource Scheduling Problem of Machines and AGVs Based on Hybrid Discrete Salp Swarm Algorithm

In a flexible manufacturing shop, the cooperation of Automated Guided Vehicles (AGVs) and machines is more in accordance with the real production situation. A scheduling problem of flexible manufacturing shop floor considering the transportation time is studied. The dual resource integrated scheduling issue with multiple AGVs and multiple machines is modeled by mixed-integer programming (MIP). An improved Hybrid Discrete Salp Swam Algorithm (HDSSA) is proposed to optimize the maximum makespan. A three-layer coding scheme based on workpiece, machine and AGV is adopted to realize the SSA adapted to the discrete combinatorial problem. The purpose of a designed heuristic initialization approach in decoding is to raise the quality of the algorithm’s initial solution. The idea of differential variation is implemented into the HDSSA to increase its global search capability through variation and crossover operators. To enhance the HDSSA’s local search ability, a variable neighborhood search depending on problem feature is introduced to the optimal individual of each iteration. To prove the effectiveness of the algorithm improvement strategy and the proposed HDSSA, comparative experiments are conducted with other algorithms through standard instances. The results of the experiments suggest the proposed approach is capable of successfully resolving the integrated scheduling problem considering transportation time.