Skateboard Motion Inspired Optimization Algorithm
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901752558649344 |
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| author | Zhang, Jincheng |
| author_facet | Zhang, Jincheng |
| contents | <p><span>In recent years, heuristic optimization algorithms have been widely used in engineering optimization, combinatorial optimization, intelligent control, and other fields. This paper proposes an intelligent optimization algorithm inspired by skateboarding, named Skateboard Motion Inspired Optimization (SMIO). This algorithm simulates the dynamic balance, freewheeling, nonlinear flipping and jumping, and impact absorption characteristics of skateboarding, transforming these physical mechanisms into a mathematical model of the optimization process. The algorithm implements search through four core operators: a propulsion operator, a dynamic center of gravity correction operator, a nonlinear flipping and jumping operator, and an impact absorption step-size adjustment operator. This paper presents a detailed mathematical model of the algorithm in plain text and provides complete pseudocode. This algorithm achieves localized and refined search while maintaining global exploration capabilities, reflecting the unique characteristics of skateboarding and providing a new approach to solving complex optimization problems</span>.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17431516 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Skateboard Motion Inspired Optimization Algorithm Zhang, Jincheng <p><span>In recent years, heuristic optimization algorithms have been widely used in engineering optimization, combinatorial optimization, intelligent control, and other fields. This paper proposes an intelligent optimization algorithm inspired by skateboarding, named Skateboard Motion Inspired Optimization (SMIO). This algorithm simulates the dynamic balance, freewheeling, nonlinear flipping and jumping, and impact absorption characteristics of skateboarding, transforming these physical mechanisms into a mathematical model of the optimization process. The algorithm implements search through four core operators: a propulsion operator, a dynamic center of gravity correction operator, a nonlinear flipping and jumping operator, and an impact absorption step-size adjustment operator. This paper presents a detailed mathematical model of the algorithm in plain text and provides complete pseudocode. This algorithm achieves localized and refined search while maintaining global exploration capabilities, reflecting the unique characteristics of skateboarding and providing a new approach to solving complex optimization problems</span>.</p> |
| title | Skateboard Motion Inspired Optimization Algorithm |
| url | https://doi.org/10.5281/zenodo.17431516 |