基于多策略融合遗传算法的柔性作业车间双目标调度优化OA

For the flexible job shop scheduling problem,a mathematical model was formulated with the optimization objectives of minimizing makespan and carbon emissions.An enhanced genetic algorithm integrating multiple strategies was proposed.A chaos-based initialization method was employed to gen-erate a high-quality population,while adaptive crossover and mutation probabilities were introduced to accelerate convergence.A Lévy flight strategy was incorporated to strengthen the global search capabili-ty,and a simulated annealing algorithm with an improved cooling curve was hybridized to enhance local search ability.Case studies and examples for verification demonstrate that compared with other algo-rithms,the proposed method not only exhibits significant advantages in reducing makespan but also achieves promising results in carbon emission optimization.