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Mycelial Search: A New Graph-Structured Metaheuristic for Optimization

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Mycelial Search (Myco), a novel graph-structured metaheuristic designed for continuous optimization problems. This method balances information sharing and diverse search directions through active tips, community-weighted flow, adaptive cord plasticity, and anchor-based injection. Myco forms an evolving spatial graph where a Louvain partition distinguishes information exchange within and between communities. Evaluations on the CEC 2022 benchmark suite showed Myco achieving competitive results against eleven established optimizers across various dimensions. AI

RANK_REASON The cluster contains a research paper detailing a new optimization algorithm. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.NE (Neural & Evolutionary) →

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Mycelial Search: A New Graph-Structured Metaheuristic for Optimization

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The cluster contains a research paper detailing a new optimization algorithm. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Mohammad Mahdi Dehshibi ·

    Mycelial Search: A Graph-Structured Metaheuristic for Continuous Optimisation

    Continuous optimisation methods need to balance sharing information and maintaining alternative search directions. In this paper, we introduce Mycelial Search (Myco), a graph-structured metaheuristic designed around active tips, community-weighted flow, adaptive cord plasticity, …

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