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针对考虑可再生能源的柔性流水车间调度问题(Flexible Flow Shop Scheduling Problem with Renewable Energy,FFSP-RE),提出了集成低碳调度策略的快速非支配排序遗传算法。根据可再生能源的发电特性,首先建立了可再生能源供电模型和FFSP-RE数学模型,然后提出了快速非支配排序遗传算法的总体流程,设计了基于操作的编码方法,提出了考虑可再生能源特性的低碳调度策略,随机选择线性次序交叉和基于位置交叉,选择反转逆序的变异算子,根据拥挤度和非支配等级选择进入下一代种群的个体。最后,通过多个数值实验,证明了所提算法能够有效求解FFSP-RE,实验结果也表明考虑可再生能源能够在保证完工时间的前提下,有效降低碳排放量。
In order to solve the problem of flexible flow shop scheduling problem with renewable energy (FFSP-RE), a fast non-dominated ranking genetic algorithm with integrated low-carbon scheduling strategy is proposed. According to the power generation characteristics of renewable energy, a renewable energy power supply model and FFSP-RE mathematical model are established firstly. Then the overall flow of fast non-dominated sequencing genetic algorithm is proposed, and the operation-based coding method is designed. Characteristics of low-carbon scheduling strategy, random selection of linear order crossover and location-based crossover, reversal of the choice of reverse mutation operator, according to the degree of congestion and non-dominated level to enter the next generation of individuals. Finally, several numerical experiments are carried out to prove that the proposed algorithm can effectively solve FFSP-RE. The experimental results also show that considering renewable energy can effectively reduce carbon emission while ensuring the completion time.