Child & Adolescent Mental Health Inspired Optimization Algorithm: A Novel Heuristic Approach

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1. Verfasser: Zhang, Jincheng
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Veröffentlicht: Zenodo 2025
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author Zhang, Jincheng
author_facet Zhang, Jincheng
contents <p><span>This paper proposes a novel metaheuristic optimization algorithm inspired by Child & Adolescent Mental Health (CAMH)—the Child & Adolescent Mental Health Inspired Optimization (CAMHIO). This algorithm uses mental health, emotion regulation, attention fluctuations, psychological resilience, and social learning as its core mechanisms. By simulating the psychological characteristics of children and adolescents, it guides the search process, achieving a dynamic balance between global exploration and local development. Unlike traditional swarm intelligence algorithms, CAMHIO introduces an original emotion-psychological resilience coupling mechanism, attention fluctuation mechanism, social sensitivity dynamic adjustment mechanism, and psychological intervention jump mechanism, thus providing a completely new set of formulas for individual position updates and behavioral regulation in mathematics. This paper comprehensively elaborates on the algorithm's design principles, mathematical formulas, mechanism innovations, and theoretical significance, providing new ideas and methods for solving future multidimensional optimization problems.</span></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17620461
institution Zenodo
language
publishDate 2025
publisher Zenodo
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spellingShingle Child & Adolescent Mental Health Inspired Optimization Algorithm: A Novel Heuristic Approach
Zhang, Jincheng
<p><span>This paper proposes a novel metaheuristic optimization algorithm inspired by Child & Adolescent Mental Health (CAMH)—the Child & Adolescent Mental Health Inspired Optimization (CAMHIO). This algorithm uses mental health, emotion regulation, attention fluctuations, psychological resilience, and social learning as its core mechanisms. By simulating the psychological characteristics of children and adolescents, it guides the search process, achieving a dynamic balance between global exploration and local development. Unlike traditional swarm intelligence algorithms, CAMHIO introduces an original emotion-psychological resilience coupling mechanism, attention fluctuation mechanism, social sensitivity dynamic adjustment mechanism, and psychological intervention jump mechanism, thus providing a completely new set of formulas for individual position updates and behavioral regulation in mathematics. This paper comprehensively elaborates on the algorithm's design principles, mathematical formulas, mechanism innovations, and theoretical significance, providing new ideas and methods for solving future multidimensional optimization problems.</span></p>
title Child & Adolescent Mental Health Inspired Optimization Algorithm: A Novel Heuristic Approach
url https://doi.org/10.5281/zenodo.17620461