An efficient dominance decomposition-based deep graph evolutionary algorithm for the expensive multi-objective optimization

Key Points

• Enhanced efficiency in multi-objective optimization is achieved by the proposed algorithm, showing improvements in performance metrics.
• Performance metrics indicate the algorithm reduces computational expenses while retaining effectiveness across various objective functions.
• The method involves a dominance decomposition approach combined with deep graph techniques for optimal solutions.
• Significant implications arise for complex optimization problems, highlighting potential applications in various fields.