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A dynamic granularity-based multi-objective evolutionary algorithm for coal mine integrated energy system dispatch optimization
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DOI：10.1016/j.eswa.2025.129142.png)
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Abstract
En 中文
• A dynamic granularity search (DGS) approach is introduced to reduce the dimensionality of large-scale optimization problems. • A diversity-enhanced environmental selection (DES) strategy is designed to maintain both global and local diversity. • Integrating DGS and DES, a new large-scale constrained multi-objective evolutionary algorithm named DGMA is developed.
Keywords:
dynamic granularity search
diversity-enhanced environmental selection
large-scale optimization
multi-objective evolutionary algorithm
constrained optimization
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W
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