Research on the optimization of ship block flexible job-shop scheduling based on improved genetic algorithm

Aiming at the ship block production scheduling problem, a mixed integer programming model for minimizing the maximum completion time considering size constraints is constructed. An improved genetic algorithm is proposed: Double-layer coding and active scheduling decoding are used to optimize process scheduling. Heuristic rules are used to initialize the population. Cross mutation strategy is designed to enhance search ability. Dynamic neighborhood optimization is realized by combining key path analysis of disjunctive graph. Simulations show that the algorithm outperforms traditional methods in terms of speed and accuracy, providing theoretical support for the flexible scheduling of ship blocks.