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Offline decision tree-based microscale evolutionary algorithm for multimodal multiobjective optimization
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AI
DOI：10.1016/j.eswa.2026.133970.png)
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Abstract
En 中文
<ul class="list">
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0001">
Proposes a novel ODT-MEA algorithm for multimodal multiobjective optimization.
</div></span></li>
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0002">
Predicts Pareto front types via offline decision trees mining population patterns.
</div></span></li>
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0003">
Outperforms state-of-the-art methods via adaptive fitness evaluation allocation.
</div></span></li>
</ul>
Keywords:
Multimodal multiobjective optimization
Offline decision tree
Evolutionary algorithm
Computational intelligence
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W
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