Micro/Nanorobotics Inspired Multi-Field Interaction Optimization: Algorithm Design and Mathematical Modeling Article Swipe
Micro/nanororobotics are intelligent robotic systems ranging from micrometers to nanometers in size, characterized by complex motion in low Reynolds number fluid environments, sensitivity to microscopic environments, self-assembly, and multi-force field response. This paper proposes an optimization algorithm based on the motion mechanism of micro/nanororobotics—the Micro/Nanorobotics Inspired Multi-Field Interaction Optimization (MNMFIO) algorithm—to simulate the nonlinear multi-force field superposition, local micro-environment perception, population adaptive distribution control, and non-Gaussian Brownian perturbation behavior of micro/nanororobotics in complex environments. The algorithm treats each candidate solution as the position of the micro/nanororobotics, and accurately describes its velocity, position update, and force field interaction mechanism through mathematical formulas. This paper derives the mathematical model of the algorithm in detail, including external forces, population interaction forces, local micro-environment forces, adaptive density control, and random perturbation mechanisms, fully reflecting the characteristics of micro/nanororobotics. The algorithm's global exploration and local exploitation capabilities, as well as its potential to escape local optima, are analyzed. This algorithm not only has clear physical simulation significance but also provides a new heuristic search method for complex optimization problems.
Related Topics
Concepts
Population
Nonlinear system
Algorithm
Computer science
Perturbation (astronomy)
Position (finance)
Brownian motion
Mathematical optimization
Heuristic
Optimization problem
Mathematics
Field (mathematics)
Mathematical model
Local optimum
Global optimization
Sensitivity (control systems)
Adaptive algorithm
Robustness (evolution)
Ranging
Complex system
Artificial intelligence
Local search (optimization)
Metadata
- Type
- preprint
- Landing Page
- https://doi.org/10.5281/zenodo.17853126
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7111031257
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7111031257Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5281/zenodo.17853126Digital Object Identifier
- Title
-
Micro/Nanorobotics Inspired Multi-Field Interaction Optimization: Algorithm Design and Mathematical ModelingWork title
- Type
-
preprintOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-08Full publication date if available
- Authors
-
Zhang Jin-chengList of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.17853126Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5281/zenodo.17853126Direct OA link when available
- Concepts
-
Population, Nonlinear system, Algorithm, Computer science, Perturbation (astronomy), Position (finance), Brownian motion, Mathematical optimization, Heuristic, Optimization problem, Mathematics, Field (mathematics), Mathematical model, Local optimum, Global optimization, Sensitivity (control systems), Adaptive algorithm, Robustness (evolution), Ranging, Complex system, Artificial intelligence, Local search (optimization)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
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