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Updated: Sep 10, 2025
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem
Yan Zheng1, Bin Guo2,3, Yongquan Zhou2,3
1Department of Science and Technology Teaching, China University of Political Science and Law, Beijing 100088, China.
Biomimetics (Basel, Switzerland)
|August 27, 2025
Summary
A novel multi-objective white shark optimizer (MOWSO) enhances sports facility location planning. This algorithm optimizes resident coverage and location efficiency, offering diverse, intelligent solutions for rural areas.
Area of Science:
- Operations Research
- Computational Intelligence
- Spatial Optimization
Background:
- The white shark optimizer (WSO) is a swarm intelligence algorithm with broad applications.
- Optimizing sports facility locations is a complex, multi-objective challenge.
Purpose of the Study:
- To propose a multi-objective white shark optimizer (MOWSO) for sports facility location problems.
- To enhance the diversity and distribution of non-dominated solutions using an archiving mechanism and Pareto optimal solution distance calculation.
Main Methods:
- Formulating the sports facility location problem as a multi-objective optimization task.
- Introducing resident coverage and the Weber problem as objective functions.
- Developing and implementing the MOWSO with an adaptive archive management strategy.
Main Results:
- MOWSO demonstrated superior performance in solution diversity and distribution compared to other algorithms on CEC 2020 benchmark functions.
- The algorithm successfully generated various optimal location schemes for rural sports facilities.
Conclusions:
- MOWSO is an effective algorithm for solving multi-objective optimization problems, particularly in spatial planning.
- The proposed method provides valuable, diverse options for rural sports facility location, promoting intelligent design and planning.
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