Improved Artificial Hummingbird Algorithm for Solving Energy-Efficient Scheduling Problem of Distributed Hybrid Flow Shop

Abstract

To tackle the challenges of time efficiency and energy consumption in the context of production diversification and green manufacturing, GDMOAHA was developed to minimize the makespan and total energy consumption. First, a problem-specific heuristic, NEH-SE, was designed to improve the initial population's diversity and quality. In addition, the golden sine strategy has been implemented to achieve a good balance between exploration and exploitation. Third, the inclusion of the Cauchy variation enhances the algorithm's ability to find optimal values. Compared with other algorithms, GDMOAHA outperforms other algorithms in terms of convergence and diversity. Therefore, it can solve the problem well.