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An escape-oriented multi-objective optimization algorithm using diverse external archives
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AI
DOI：10.1016/j.eswa.2025.130953.png)
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Abstract
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• A multi-objective optimization algorithm based on crowd evacuation behavior is developed. • Complementary subgroups and inferior-solution perturbation accelerate early exploration. • Multi-archive guidance exchanges info between subgroups for diverse Pareto front. • Tested on ZDT/WFG/DTLZ/CEC2019 and three engineering cases, it performs best.
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