关键词: 可再生能源, 分布式装配流水车间调度, 低碳调度, 带精英策略的非支配排序遗传算法, 模拟退火

Abstract: To achieve the green manufacturing transformation of enterprises,a mathematical model for the Distributed Assembly Permutation Flowshop Scheduling Problem with Renewable Energy (DAPFSP-RE) was constructed,aiming to minimize the maximum completion time and total carbon emissions while ensuring production efficiency.A Two-stage NSGA-Ⅱ and Simulated Annealing algorithm (TNSA) was proposed to solve the problem,which included a decoding method incorporating low-carbon factory selection strategies and energy scheduling.In the first stage,a reverse learning initialization method was adopted to generate a dual-population structure,and the solution space was searched through crossover,mutation and a binary tournament selection operation with adaptive elite retention.In the second stage,the AMOSA algorithm was used to perform simulated annealing operations on the non-dominated solution set obtained in the first stage to escape local optima.Through simulation experiments on cases of different scales,the important role of renewable energy in reducing carbon emissions during the production process and the effectiveness and competitiveness of the proposed algorithm for solving DAPFSP-RE were verified.

Key words: renewable energy, distributed assembly permutation flowshop scheduling, low-carbon scheduling, NSGA-Ⅱ, simulated annealing