福建师范大学学报（自然科学版）2025，Vol.41Issue(6)：34-44,53,12.DOI:10.12046/j.issn.1000-5277.2024110010
基于自适应贪心-遗传混合算法的健身中心选址方法
Fitness Center Site Selection Based on an Adaptive Greedy-Genetic Algorithm
摘要
Abstract
In the context of the rapid development of national fitness,a multi-objective site se-lection method based on an adaptive greedy-genetic algorithm(AGGA)is proposed for fitness center site selection.This method aims to optimally lay out fitness centers to maximize the coverage of serv-ice points and comprehensive benefits.Firstly,considering factors such as population density,traf-fic convenience,and fitness demand,the Huff gravity model is used to evaluate the attractiveness of fitness centers to residents,and the configuration scheme of fitness centers is optimized in accord-ance with national standards.Secondly,to avoid the blindness and randomness of mutation in ge-netic algorithms(GA),greedy strategies are introduced to effectively improve the stability of AGGA algorithm in solving complex site selection problems.Experimental results show that the AGGA can effectively optimize the selection and planning scheme of fitness centers under different coverage ra-dius conditions.Compared with classical heuristic algorithms,the proposed method increases the comprehensive benefits by 5.56%～9.28%under a 5 km coverage radius,providing residents with a high-quality fitness service experience.关键词
健身中心/Huff重力模型/选址优化/自适应遗传算法Key words
fitness centers/Huff gravity model/site selection optimization/adaptive genetic algorithm分类
计算机与自动化引用本文复制引用
陈龙强,林海潮,郑意..基于自适应贪心-遗传混合算法的健身中心选址方法[J].福建师范大学学报（自然科学版）,2025,41(6):34-44,53,12.基金项目
国家自然科学基金项目(62072108) （62072108）
福建省科技经济融合服务平台项目(2023XRH001) （2023XRH001）
福厦泉国家自主创新示范区协同创新平台项目(2022FX5) （2022FX5）
福建省高校产学合作资助项目(2022H6024,2021H6026) （2022H6024,2021H6026）
