Work

Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem

Year: 2025

Type: article

Abstract: A swarm intelligence optimization algorithm called white shark optimizer (WSO) has been proposed and successfully applied in regard to many aspects. In this paper, the location problem of sports facilities is regarded as a multi-objective problem, and the number of residents covered by sports facilities and the Weber problem are introduced as objective functions. A multi-objective white shark optimizer (MOWSO) is proposed, and MOWSO introduced an archived mechanism to store the non-dominated solutions obtained by the algorithm. When the Pareto solutions in the archive overflow, the solutions are removed by calculating the true distance of the Pareto optimal solution. The performance of the MOWSO is verified on CEC 2020 benchmark functions, and the results show that the proposed MOWSO is better than other algorithms in the diversity and distribution of solutions. The MOWSO is applied to solve the rural sports facilities location problem, and a variety of different sports facilities location schemes are obtained. It can provide a variety of options for the location of rural sports facilities, and promote the intelligent design of sports facilities.

Source: Biomimetics

DOI: 10.3390/biomimetics10080537

Authors: Yan Zheng, Bin Guo, Yongquan Zhou

Institutions: China University of Political Science and Law, Guangxi Minzu University

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,654

Funder: National Natural Science Foundation of China