Multi-tracker Optimization Algorithm: A General Algorithm for Solving Engineering Optimization Problems

被引:31
|
作者
Zakeri, Ehsan [1 ]
Moezi, Seyed Alireza [1 ]
Bazargan-Lari, Yousef [2 ]
Zare, Amin [1 ]
机构
[1] Islamic Azad Univ, Shiraz Branch, Young Researchers & Elite Club, Shiraz, Iran
[2] Islamic Azad Univ, Shiraz Branch, Dept Mech Engn, Shiraz, Iran
关键词
MTOA; Engineering optimization problems; Dynamic optimization problems; PARTICLE SWARM OPTIMIZATION; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHMS; CRACK DETECTION; OPTIMAL-DESIGN; SEARCH; SIMULATION; BEAM; BEES;
D O I
10.1007/s40997-016-0066-9
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this paper, a new computational population-based optimization algorithm, which is designed based on the advantages and disadvantages of other evolutionary optimization algorithms introduced so far, is proposed. This new algorithm, which is named as "multi-tracker optimization algorithm," due to a multi-level structure of trackers within it, has some unique features, such as increasing the accuracy of the optimal point and continuous local search after convergence in order to escape from local minima simultaneously. Another important advantage of this algorithm is optimizing time-varying dynamical problems and tracking the optimal point. These characteristics make the algorithm very efficient for optimization problems, especially in the field of engineering. For a thorough investigation and comparison of this algorithm with other efficient optimization algorithms, different optimization problems such as static, dynamic, unconstrained and constrained, each of which has different challenges, are considered. The results of applying this algorithm on the abovementioned basic problems show the superiority of this algorithm over other efficient evolutionary algorithms.
引用
收藏
页码:315 / 341
页数:27
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