摘要
为衡量消防救援站在不同时间内提供的救援服务质量,基于火灾风险等级引入时效性评价函数,构建考虑时效性和经济性的双目标选址模型。针对新模型属于NP难问题特点,设计元胞阴阳平衡优化算法进行求解。寻优个体既在阴阳平衡优化算法搜索空间进行全局探索,又在元胞空间利用演化规则在邻居范围内进行局部开发。实验证明了新模型的可行性和有效性,与蝙蝠算法、蜂群算法、和声搜索算法、NGSA-Ⅱ和元胞蚁群优化算法的比较表明,新算法在非劣解集的收敛性、多样性、分布均匀性以及计算速度方面优势显著。
To measure the quality of rescue services provided by fire rescue stations at different times, the timeliness evaluation function based on fire risk level is introduced. Bi-objective location model that considers both timeliness and economy is constructed. Aiming at the characteristics of the new model that is NP-hard, cellular Yin-Yang pair optimization algorithm is proposed. The individual not only performs global exploration in the search space of the Yin-Yang pair optimization algorithm, but also uses evolution rules in the cellular space to perform local exploitation within the neighborhood. The experiments prove the feasibility and effectiveness of the new model. The performance of algorithm is compared with bat algorithm, bee colony algorithm, harmony search algorithm, NGSA-Ⅱ and cellular ant colony optimization algorithm. The results show that the new algorithm is superior to the other five methods in terms of convergence, diversity, uniformity of distribution for the set of non-inferior solutions and calculation speed.
作者
许秋艳
马良
刘勇
XUQiu-yan;MA Liang;LIU Yong(Schoolof Management,University of Shanghai for Science and Technology,Shanghai 200093,China;College of Information Engineering,Yancheng Institute of Technology,Yancheng 224051,China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2022年第12期31-37,共7页
Operations Research and Management Science
基金
上海市软科学研究重点项目(18692110500)
上海市哲学社会科学规划课题(2019BGL014)。
关键词
消防救援站选址
时效性
经济性
阴阳平衡优化算法
元胞自动机
fire rescue facility location
timeliness
economy
Yin-Yang pair optimization algorithm
cellular automata
