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Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource

Yibo Han1, Pu Han2, Bo Yuan3

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|April 24, 2023
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Summary
This summary is machine-generated.

This study introduces a novel emergency resource scheduling model using Vague set theory and adaptive grid particle swarm optimization. The new model significantly improves efficiency and accuracy in handling emergencies compared to traditional methods.

Keywords:
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Area of Science:

  • Operations Research
  • Artificial Intelligence
  • Emergency Management

Background:

  • Traditional resource scheduling systems struggle with slow decision-making, especially during emergencies.
  • Existing methods face significant disadvantages when addressing unexpected events like fires or earthquakes.
  • Intelligent scheduling systems heavily rely on effective scheduling algorithms.

Purpose of the Study:

  • To develop an advanced multi-objective emergency resource scheduling model.
  • To address the limitations of traditional resource scheduling in dynamic and uncertain environments.
  • To enhance the response capabilities for critical events through optimized resource allocation.

Main Methods:

  • Integration of Vague set theory for handling uncertainty.
  • Application of adaptive grid particle swarm optimization for multi-objective problem-solving.
  • Construction of a novel multi-objective emergency resource scheduling model.

Main Results:

  • The proposed model demonstrates higher resolution accuracy and more reasonable resource allocation.
  • The model achieves significantly improved efficiency and speed in dealing with emergency events.
  • Handling speed increased by over 3.82 times compared to conventional fuzzy theory models.

Conclusions:

  • The Vague set theory and adaptive grid particle swarm optimization-based model offers superior performance for emergency resource scheduling.
  • This approach effectively manages uncertainty and optimizes resource allocation during critical incidents.
  • The developed model represents a significant advancement over traditional and fuzzy theory-based scheduling methods.