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An independence-cooperation-competition framework for constrained multi-objective optimization
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DOI：10.1016/j.asoc.2026.116249.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="p0035">
An independence-cooperation-competition framework that includes three stages and three populations (ICCMO) is proposed.
</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="p0040">
A dual-distance diversity mechanism is established, which uses the Euclidean distance and angular distance.
</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="p0045">
The operator competition strategy is used to select the best operator in order to conserve computational resources.
</div></span></li>
</ul>
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W