Mechanical Designer Inspired Optimization Algorithm
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901784537071616 |
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| author | Zhang, Jincheng |
| author_facet | Zhang, Jincheng |
| contents | <p><span>Optimization algorithms have wide applications in engineering design, resource allocation, mechanical structure optimization, and other fields. However, existing algorithms still face challenges with local convergence and insufficient global search capabilities when dealing with complex optimization problems characterized by high dimensions, multiple constraints, and module coupling. This paper proposes a heuristic optimization algorithm based on the thinking of mechanical designers: the Mechanical Designer Inspired Optimization (MDIO) algorithm. This algorithm draws on the core thinking characteristics of mechanical designers in actual design, including structural layering, module fine-tuning, coupling perception, design memory, and multi-objective compromise, and abstracts them into a mathematical model. The algorithm innovatively introduces the module mechanical sensitivity coefficient (MSC), local-global coupling correction (LGCC), design memory entropy (DME), and a multi-objective adaptive compromise mechanism to achieve efficient search for complex optimization problems. This paper details the algorithm's principles, mathematical formulas, and process, providing new insights for optimizing high-dimensional complex systems.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17197095 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Mechanical Designer Inspired Optimization Algorithm Zhang, Jincheng <p><span>Optimization algorithms have wide applications in engineering design, resource allocation, mechanical structure optimization, and other fields. However, existing algorithms still face challenges with local convergence and insufficient global search capabilities when dealing with complex optimization problems characterized by high dimensions, multiple constraints, and module coupling. This paper proposes a heuristic optimization algorithm based on the thinking of mechanical designers: the Mechanical Designer Inspired Optimization (MDIO) algorithm. This algorithm draws on the core thinking characteristics of mechanical designers in actual design, including structural layering, module fine-tuning, coupling perception, design memory, and multi-objective compromise, and abstracts them into a mathematical model. The algorithm innovatively introduces the module mechanical sensitivity coefficient (MSC), local-global coupling correction (LGCC), design memory entropy (DME), and a multi-objective adaptive compromise mechanism to achieve efficient search for complex optimization problems. This paper details the algorithm's principles, mathematical formulas, and process, providing new insights for optimizing high-dimensional complex systems.</span></p> |
| title | Mechanical Designer Inspired Optimization Algorithm |
| url | https://doi.org/10.5281/zenodo.17197095 |