Black Hole Mechanics Optimization: a novel meta-heuristic algorithm

被引：0
作者：
Kaveh A. [1 ]
Seddighian M.R. [1 ]
Ghanadpour E. [1 ]
机构：
[1] School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran
来源：
Asian Journal of Civil Engineering | 2020年 / 21卷 / 7期
关键词：
Black hole mechanics; Covariance matrix; Meta-heuristic algorithms; Optimization; Optimum design;
D O I：
10.1007/s42107-020-00282-8
中图分类号：
学科分类号：
摘要：
In this paper, a new meta-heuristic algorithm is proposed. The proposed method contains a mathematical kernel and a physical simulation. The mathematical kernel computes the optimum direction of each variable subjected to the cost function. Then, it conducts generated data to the detected path. Besides, the physical simulation controls the exploration procedure as well as the exploitation. The simulating process is based on the mechanics of black holes. In the structure of the proposed algorithm, there are two types of black holes. The first is a Kerr black hole forming a circular gravity filed to explore all the problem search space. The other one is a Schwarzschild black hole exploiting the data in the vicinity of its singularity. Eventually, the potency and efficiency of the new algorithm are investigated using several mathematical and four benchmark skeletal structures. © 2020, Springer Nature Switzerland AG.
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收藏
页码：1129 / 1149
页数：20
相关论文
共 76 条
[1]  
Manual of steel construction: Allowable stress design, (1989)
[2]  
Manual of steel construction: Load resistance factor design, (2001)
[3]  
Askarzadeh A., Rezazadeh A., A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: Bird mating optimizer, International Journal of Energy Research, 37, 10, pp. 1196-1204, (2013)
[4]  
Atashpaz-Gargari E., Lucas C., Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition, IEEE Congress on Evolutionary Computation, (2007)
[5]  
Balochian S., Baloochian H., Social mimic optimization algorithm and engineering applications, Expert Systems with Applications, 134, pp. 178-191, (2019)
[6]  
Bekenstein J.D., Black holes and entropy, Physical review D: Particles and Fields, 7, 8, (1973)
[7]  
Carroll S., Spacetime and geometry: An introduction to general relativity, (2019)
[8]  
Carvalho J., Lemonge A., Carvalho E., Hallak P., Bernardino H., Truss optimization with multiple frequency constraints and automatic member grouping, Structural and Multidisciplinary Optimization, (2017)
[9]  
Chen W., Zhang J., Lin Y., Chen N., Zhan Z.-H., Chung H.S., Li Y., Shi Y., Particle swarm optimization with an aging leader and challengers, IEEE Transactions on Evolutionary Computation, 17, pp. 241-258, (2013)
[10]  
Davies P.C., Thermodynamics of black holes, Reports on Progress in Physics, 41, 8, (1978)
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