This invention belongs to the field of
hybrid flow shop scheduling technology in intelligent manufacturing, and particularly relates to a
hybrid flow shop scheduling optimization method considering periodic
preventive maintenance. The method constructs a DCABC-CP
hybrid algorithm that integrates dual-
population cooperative artificial bee colony and
constraint programming. Through parameter initialization, dual-
population hybrid encoding initialization, iterative optimization using hired bees, observer bees, and scout bees, adaptive
population cooperation based on Thompson sampling multi-armed
slot machine, forward and reverse decoding re-evaluation, and problem-specific local search, when the
algorithm reaches 40% of its total
execution time, the current optimal solution is imported into the CP model for precise optimization. Finally, it outputs a scheduling scheme that minimizes the maximum
completion time while satisfying the periodic
preventive maintenance constraint. This invention effectively balances global search and local optimization, enhances the ability to
handle maintenance constraints, and significantly outperforms traditional algorithms in terms of solution efficiency and quality, making it suitable for large-scale hybrid
flow shop scheduling scenarios.