A Study on Site Selection for Regional Air Rescue Centers Based on Multi-Objective Jellyfish Search Algorithm

Area of Science:

• Operations Research
• Emergency Management
• Spatial Analysis

Background:

• Air emergency rescue is crucial for national strength and social emergency response.
• Existing models often focus on single objectives, limiting comprehensive site selection.
• Enhancing regional air rescue capabilities requires advanced planning and resource deployment.

Purpose of the Study:

• To develop a novel multi-objective siting model for air emergency rescue centers.
• To design an efficient algorithm for solving the multi-objective optimization problem.
• To provide a feasible and accurate method for regional air rescue station site selection.

Main Methods:

• A multi-objective optimization function was established, incorporating construction cost, response time, and radiation range.
• A radiation function was developed to assess candidate airport coverage.
• The multi-objective jellyfish search algorithm (MOJS) was used to find Pareto optimal solutions.
• MATLAB and ArcGIS tools were employed for algorithm implementation and spatial analysis.

Main Results:

• The proposed model effectively integrates multiple objectives for site selection.
• The MOJS algorithm successfully identified Pareto optimal solutions.
• Case study analysis in China demonstrated the model's ability to achieve desired site selection goals.
• Site selection results were visualized using ArcGIS, prioritizing construction costs.

Conclusions:

• The novel multi-objective siting model provides a robust framework for air emergency rescue station selection.
• The integrated approach enhances regional emergency response capabilities by optimizing key parameters.
• This research offers a feasible and accurate methodology for future air rescue infrastructure planning.