Abstract: A Hybrid Pathfinder Algorithm (HPFA) is proposed for solving the green flow shop scheduling problem with limited buffers and energy threshold constraints (GFSSP_LBET). The optimization criteria are to minimize the total energy consumption and the makespan. In order to enhance the global search ability of HPFA, a distance-based selection scheme is designed to determine each pathfinder's followers to ensure that the near regions of any pathfinder can get a certain search. A self-learning search strategy integrating multiple operations is designed to perform multi-neighborhood search on the updated pathfinders, which can improve the local exploitation ability of HPFA. Simulation experiments show that the presented improvement strategies can effectively enhance the performance of HPFA and also verify the effectiveness and robustness of HPFA for dealing with the GFSSP_LBET.

Key words: hybrid pathfinder algorithm, limited buffers, flow shop scheduling problem, total energy consumption, energy threshold constraints