碳交易下分布式双资源柔性作业车间节能调度

在碳交易政策的背景下,企业需统筹考虑效率和环境因素,以实现企业效益最大化。文章研究了考虑机器和工人的分布式双资源柔性作业车间节能调度问题和方案,以最短完工时间、最小能耗和碳交易成本为目标,建立了混合整数规划模型。依据此问题多资源约束的特点,研究设计了一种改进麻雀搜索算法,嵌入了"工厂—工序—机器&工人"三层编码的主动解码策略,提高了资源利用率。为了扩大搜索空间,在算法中引入了6种局部搜索策略,通过2、3、4个工厂共30组算例,将改进的麻雀搜索算法与其他3种算法进行对比。实验结果表明,改进的麻雀搜索算法优于其他对比的算法,对比结果验证了此改进算法的有效性。

Energy-Efficient Scheduling of Distributed Dual-Resource Flexible Job Shop Under the Background of Carbon Trading Policy

In the context of carbon trading policy, enterprises need to consider efficiency and environmental factors integrally to maximize their benefits. In this paper, an energy-saving scheduling problem for distributed dual-resource flexible job shop considering machines and workers is investigated, and a mixed-integer planning model is developed, with the objectives of minimizing the makespan, energy consumption and carbon trading cost. Aiming at the multi-resource constraints of this problem, an improved sparrow search algorithm is designed in this paper, which embeds an active decoding strategy based on the three-layer encoding of "factory-operation-machine&worker" to improve the resource utilization rate. To expand search space, 6 local search strategies are introduced into the algorithm. The improved sparrow search algorithm is compared with the other three algorithms through 30 sets of instances in 2, 3 and 4 factories. The results show that the improved sparrow search algorithm is superior to the other comparison algorithms, and the comparison results verify the effectiveness of this improved algorithm.