Research on modeling and algorithm of resource allocation optimization based on multi-factor constraints

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Optimizing resource allocation under constraints significantly improves system efficiency and stability.
The forecasting-scheduling modeling approach effectively identifies influencing factors and simulates system responses.
Regression and growth models reveal non-linear behavior, enhancing understanding of resource constraints.
This framework has potential applications across various industries facing resource allocation challenges.

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Research demonstrates enhanced resource allocation efficiency in agriculture and energy, highlighting its adaptability under various constraints.

Gonghao Li (2025) studied this question.

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Research demonstrates enhanced resource allocation efficiency in agriculture and energy, highlighting its adaptability under various constraints.